Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset

OBJECTIVE

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci.

METHODS

We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset.

RESULTS

In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM.

SIGNIFICANCE

It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Patients with Heart Failure: Internet Use and Mobile Health Perceptions

BACKGROUND

Heart failure is a complex clinical syndrome noted on approximately 1 in 8 death certificates in the United States. Vital to reducing complications of heart failure and preventing hospital readmissions is adherence to heart failure self-care routines. Mobile health offers promising opportunities for enhancing self-care behaviors by facilitating tracking and timely reminders.

OBJECTIVE

We sought to investigate three characteristics of heart failure patients with respect to their heart failure self-care behaviors: (1) internet use to search for heart failure information; (2) familiarity with mobile health apps and devices; and (3) perceptions of using activity trackers or smartwatches to aid in their heart failure self-care.

METHODS

Forty-nine heart failure patients were asked about their internet and mobile health usage. The structured interview included questions adapted from the Health Information National Trends Survey.

RESULTS

Over 50% of the patients had utilized the internet to search for heart failure information in the past 12 months, experience using health-related apps, and thoughts that an activity tracker or smartwatch could help them manage heart failure. Qualitative analysis of the interviews revealed six themes: trust in their physicians, alternatives to mobile health apps, lack of need for mobile health devices, financial barriers to activity tracker and smartwatch ownership, benefits of tracking and reminders, and uncertainty of their potential due to lack of knowledge.

CONCLUSIONS

Trust in their physicians was a major factor for heart failure patients who reported not searching for health information on the internet. While those who used mobile health technologies found them useful, patients who did not use them were generally unaware of or unknowledgeable about them. Considering patients' preferences for recommendations from their physicians and tendency to search for heart failure information including treatment and management options, patient-provider discussions about mobile health may improve patient knowledge and impact their usage.

The effect of dose-interval on antibody response to mRNA COVID-19 vaccines: a prospective cohort study

Background

Vaccination against COVID-19 is highly effective in preventing severe disease and hospitalization, but primary COVID mRNA vaccination schedules often differed from those recommended by the manufacturers due to supply chain issues. We investigated the impact of delaying the second dose on antibody responses to COVID mRNA-vaccines in a prospective cohort of health-care workers in Quebec.

Methods

We recruited participants from the McGill University Health Centre who provided serum or participant-collected dried blood samples (DBS) at 28-days, 3 months, and 6 months post-second dose and at 28-days after a third dose. IgG antibodies to SARS-CoV2 spike (S), the receptor-binding domain (RBD), nucleocapsid (N) and neutralizing antibodies to the ancestral strain were assessed by enzyme-linked immunosorbent assay (ELISA). We examined associations between long (≤89 days) versus short (<89 days) between-dose intervals and antibody response through multivariable mixed-effects models adjusted for age, sex, prior covid infection status, time since vaccine dose, and assay batch.

Findings

The cohort included 328 participants who received up to three vaccine doses (>80% Pfizer-BioNTech). Weighted averages of the serum (n=744) and DBS (n=216) cohort results from the multivariable models showed that IgG anti-S was 31% higher (95% CI: 12% to 53%) and IgG anti-RBD was 37% higher (95% CI: 14% to 65%) in the long vs. short interval participants, across all time points.

Interpretation

Our study indicates that extending the covid primary series between-dose interval beyond 89 days (approximately 3 months) provides stronger antibody responses than intervals less than 89 days. Our demonstration of a more robust antibody response with a longer between dose interval is reassuring as logistical and supply challenges are navigated in low-resource settings.

Perspectives, experiences, and concerns with cyclical vomiting syndrome: Insights from online targeted-disease forums

INTRODUCTION

There is limited research examining the biopsychosocial impact of cyclic vomiting syndrome (CVS) on patients. This study aims to assess individuals' experiences, fears, and concerns associated with CVS and the impact of CVS on their daily lives.

METHODS

We employed social netnography to analyze publicly available posts related to CVS that were identified from six US online forums and Twitter. A randomly selected sub-cohort of posts per pre-defined criteria was first qualitatively analyzed using an inductive thematic approach. Then, machine learning topic modeling was applied to explore themes in an unsupervised manner for the entire corpus of posts. Afterward, findings from the qualitative and quantitative approaches were integrated to generate a thematic network.

RESULTS

Based on the 39,179 collected posts, seven domain themes were identified. Overall, 41.4% of the posts were related to "biopsychosocial burden" of CVS, including physical impact, psychological impact, and social impact. In 22.3% of posts, individuals shared their experience of "interactions with the healthcare system", and 14.2% of posts were related to "perceived CVS triggers." Individuals also shared "solutions to alleviate their symptoms" and "mental health needs" in 10.2% and 8.8% of posts, respectively. Finally, 6.1% of the posts were about "seeking/sharing support" with others.

DISCUSSION

This is the first social netnography study to describe the in-depth experiences of individuals living with CVS and the marked impact on their physical, mental, and social health. The study also highlights the unmet need for effective therapies, both pharmacological and non-pharmacological, to alleviate the biopsychosocial impact of CVS.

Evaluating Deep Learning Performance for P300 Neural Signal Classification

P300 event-related potential (ERP) signals are useful neurological biomarkers, and their accurate classification is important when studying the cognitive functions in patients with neurological disorders. While many studies have proposed models for classifying these signals, results have been inconsistent. As a result, a consensus has not yet been reached on the optimal model for this classification. In this study, we evaluated the performance of classic machine learning and novel deep learning methods for P300 signal classification in both within and across subject training scenarios across a dataset of 75 subjects. Although the deep learning models attained high attended event classification F1 scores, they did not outperform Stepwise Linear Discriminant Analysis (SWLDA) in the within-subject paradigm. In the across-subject paradigm, however, EEG-Inception was able to significantly outperform SWLDA. These results suggest that deep learning models may provide a general model that do not require subject-specific training and calibration in clinical settings.

Patient-level thyroid cancer classification using attention multiple instance learning on fused multi-scale ultrasound image features

For patients with thyroid nodules, the ability to detect and diagnose a malignant nodule is the key to creating an appropriate treatment plan. However, assessments of ultrasound images do not accurately represent malignancy, and often require a biopsy to confirm the diagnosis. Deep learning techniques can classify thyroid nodules from ultrasound images, but current methods depend on manually annotated nodule segmentations. Furthermore, the heterogeneity in the level of magnification across ultrasound images presents a significant obstacle to existing methods. We developed a multi-scale, attention-based multiple-instance learning model which fuses both global and local features of different ultrasound frames to achieve patient-level malignancy classification. Our model demonstrates improved performance with an AUROC of 0.785 (p<0.05) and AUPRC of 0.539, significantly surpassing the baseline model trained on clinical features with an AUROC of 0.667 and AUPRC of 0.444. Improved classification performance better triages the need for biopsy.

Multi-site, Multi-domain Airway Tree Modeling

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and extensive clinical efforts for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Both quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage (https://atm22.grand-challenge.org/).

CTP-based estimated ischemic core: A comparative multicenter study between Olea and RAPID software

BACKGROUND AND PURPOSE

CTP is increasingly used to assess eligibility for endovascular therapy (EVT) in patients with large vessel occlusions (LVO). There remain variability and inconsistencies between software packages for estimation of ischemic core. We aimed to use heterogenous data from four stroke centers to perform a comparative analysis for CTP-estimated ischemic core between RAPID (iSchemaView) and Olea (Olea Medical).

METHODS

In this retrospective multicenter study, patients with anterior circulation LVO who underwent pretreatment CTP, successful EVT (defined TICI ≥ 2b), and follow-up MRI included. Automated CTP analysis was performed using Olea platform [rCBF < 25% and differential time-to-peak (dTTP)>5s] and RAPID (rCBF < 30%). The CTP estimated core volumes were compared against the final infarct volume (FIV) on post treatment MRI-DWI.

RESULTS

A total of 151 patients included. The CTP-estimated ischemic core volumes (mean ± SD) were 18.7 ± 18.9 mL on Olea and 10.5 ± 17.9 mL on RAPID significantly different (p < 0.01). The correlation between CTP estimated core and MRI final infarct volume was r = 0.38, p < 0.01 for RAPID and r = 0.39, p < 0.01 for Olea. Both software platforms demonstrated a strong correlation with each other (r = 0.864, p < 0.001). Both software overestimated the ischemic core volume above 70 mL in 4 patients (2.6%).

CONCLUSIONS

Substantial variation between Olea and RAPID CTP-estimated core volumes exists, though rates of overcalling of large core were low and identical. Both showed comparable core volume correlation to MRI infarct volume.

Perfusion Collateral Index versus Hypoperfusion Intensity Ratio in Assessment of Collaterals in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Perfusion-based collateral indices such as the perfusion collateral index and the hypoperfusion intensity ratio have shown promise in the assessment of collaterals in patients with acute ischemic stroke. We aimed to compare the diagnostic performance of the perfusion collateral index and the hypoperfusion intensity ratio in collateral assessment compared with angiographic collaterals and outcome measures, including final infarct volume, infarct growth, and functional independence.

MATERIALS AND METHODS

Consecutive patients with acute ischemic stroke with anterior circulation proximal arterial occlusion who underwent endovascular thrombectomy and had pre- and posttreatment MRI were included. Using pretreatment MR perfusion, we calculated the perfusion collateral index and the hypoperfusion intensity ratio for each patient. The angiographic collaterals obtained from DSA were dichotomized to sufficient (American Society of Interventional and Therapeutic Neuroradiology [ASITN] scale 3-4) versus insufficient (ASITN scale 0-2). The association of collateral status determined by the perfusion collateral index and the hypoperfusion intensity ratio was assessed against angiographic collaterals and outcome measures.

RESULTS

A total of 98 patients met the inclusion criteria. Perfusion collateral index values were significantly higher in patients with sufficient angiographic collaterals (P < .001), while there was no significant (P = .46) difference in hypoperfusion intensity ratio values. Among patients with good (mRS 0-2) versus poor (mRS 3-6) functional outcome, the perfusion collateral index of ≥ 62 was present in 72% versus 31% (P = .003), while the hypoperfusion intensity ratio of ≤0.4 was present in 69% versus 56% (P = .52). The perfusion collateral index and the hypoperfusion intensity ratio were both significantly predictive of final infarct volume, but only the perfusion collateral index was significantly (P = .03) associated with infarct growth.

CONCLUSIONS

Results show that the perfusion collateral index outperforms the hypoperfusion intensity ratio in the assessment of collateral status, infarct growth, and determination of functional outcomes.

Results of the Stop the Spread Ottawa (SSO) cohort study: a Canadian urban-based prospective evaluation of antibody responses and neutralisation efficiency to SARS-CoV-2 infection and vaccination

BACKGROUND

Predictors of COVID-19 vaccine immunogenicity and the influence of prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection require elucidation.

METHODS

Stop the Spread Ottawa is a prospective cohort of individuals at-risk for or who have been infected with SARS-CoV-2, initially enrolled for 10 months beginning October 2020. This cohort was enriched for public-facing workers. This analysis focuses on safety and immunogenicity of the initial two doses of COVID-19 vaccine.

RESULTS

Post-vaccination data with blood specimens were available for 930 participants. 22.8% were SARS-CoV2 infected prior to the first vaccine dose. Cohort characteristics include: median age 44 (IQR: 22-56), 66.6% women, 89.0% white, 83.2% employed. 38.1% reported two or more comorbidities and 30.8% reported immune compromising condition(s). Over 95% had detectable IgG levels against the spike and receptor binding domain (RBD) 3 months post second vaccine dose. By multivariable analysis, increasing age and high-level immune compromise predicted diminishing IgG spike and RBD titres at month 3 post second dose. IgG spike and RBD titres were higher immediately post vaccination in those with SARS-CoV-2 infection prior to first vaccination and spike titres were higher at 6 months in those with wider time intervals between dose 1 and 2. IgG spike and RBD titres and neutralisation were generally similar by sex, weight and whether receiving homogeneous or heterogeneous combinations of vaccines. Common symptoms post dose 1 vaccine included fatigue (64.7%), injection site pain (47.5%), headache (27.2%), fever/chills (26.2%) and body aches (25.3%). These symptoms were similar with subsequent doses.

CONCLUSION

The initial two COVID-19 vaccine doses are safe, well-tolerated and highly immunogenic across a broad spectrum of vaccine recipients including those working in public facing environments.

Latent diffusion augmentation enhances deep learning analysis of neuro-morphology in limbal stem cell deficiency

Introduction

Limbal Stem Cell Deficiency (LSCD) is a blinding corneal disease characterized by the loss of function or deficiency in adult stem cells located at the junction between the cornea and the sclera (i.e., the limbus), namely the limbal stem cells (LSCs). Recent advances in in vivo imaging technology have improved disease diagnosis and staging to quantify several biomarkers of in vivo LSC function including epithelial thickness measured by anterior segment optical coherence tomography, and basal epithelial cell density and subbasal nerve plexus by in vivo confocal microscopy. A decrease in central corneal sub-basal nerve density and nerve fiber and branching number has been shown to correlate with the severity of the disease in parallel with increased nerve tortuosity. Yet, image acquisition and manual quantification require a high level of expertise and are time-consuming. Manual quantification presents inevitable interobserver variability.

Methods

The current study employs a novel deep learning approach to classify neuron morphology in various LSCD stages and healthy controls, by integrating images created through latent diffusion augmentation. The proposed model, a residual U-Net, is based in part on the InceptionResNetV2 transfer learning model.

Results

Deep learning was able to determine fiber number, branching, and fiber length with high accuracy (R2 of 0.63, 0.63, and 0.80, respectively). The model trained on images generated through latent diffusion on average outperformed the same model when trained on solely original images. The model was also able to detect LSCD with an AUC of 0.867, which showed slightly higher performance compared to classification using manually assessed metrics.

Discussion

The results suggest that utilizing latent diffusion to supplement training data may be effective in bolstering model performance. The results of the model emphasize the ability as well as the shortcomings of this novel deep learning approach to predict various nerve morphology metrics as well as LSCD disease severity.

Patients' Perspectives, Experiences, and Concerns With Perianal Fistulae: Insights From Online Targeted-Disease Forums

Background

Perianal fistulae can undermine physical, emotional, and social well-being in patients with Crohn's disease and are challenging to manage. Social media offers a rich opportunity to gain an in-depth understanding of the impact of perianal fistulae on patients' daily lives outside of controlled environments. In this study, we conducted social media analytics to examine patients' experiences with perianal fistulae and assessed the impact of perianal fistulae on patients' behavior and overall well-being.

Methods

We used a mixed-method approach to examine 119 986 publicly available posts collected from 10 Crohn's disease forums in the United States between January 01, 2010 and January 01, 2020. Discussions related to Crohn's perianal fistulae were retrieved. We randomly selected 700 posts and qualitatively analyzed them using an inductive thematic approach. We then applied a latent Dirichlet allocation probabilistic topic model to explore themes in an unsupervised manner on the collection of 119 986 posts.

Results

In the qualitative analysis, 5 major themes were identified: (1) burden of perianal fistula; (2) challenges associated with treatment; (3) online information seeking and sharing; (4) patient experiences with treatments; and (5) patients' apprehension about treatments. In the quantitative analysis, the percentages of posts related to the major themes were (1) 20%, (2) 29%, (3) 66%, and (4) 28%, while the topic model did not identify theme 5.

Conclusions

Social media reveals a dynamic range of themes governing patients' perspectives and experiences with Crohn's perianal fistulae. In addition to the biopsychosocial burden, patients frequently express dissatisfaction with current treatments and often struggle to navigate among available management options.

Antibody neutralization capacity after coronavirus disease 2019 vaccination in people with HIV in Canada

OBJECTIVES

Many vaccines require higher/additional doses or adjuvants to provide adequate protection for people with HIV (PWH). Here, we compare coronavirus disease 2019 (COVID-19) vaccine-induced antibody neutralization capacity in PWH vs. HIV-negative individuals following two vaccine doses.

DESIGN

In Canadian prospective observational cohorts, including a multicentre study of PWH receiving at least two COVID-19 vaccinations (mRNA or ChAdOx1-S), and a parallel study of HIV-negative controls (Stop the Spread Ottawa Cohort), we measured vaccine-induced neutralization capacity 3 months post dose 2 (±1 month).

METHODS

COVID-19 neutralization efficiency was measured by calculating the half maximal inhibitory dilution (ID50) using a high-throughput protein-based neutralization assay for Ancestral (Wuhan), Delta and Omicron (BA.1) spike variants. Univariable and multivariable quantile regression were used to compare COVID-19-specific antibody neutralization capacity by HIV status.

RESULTS

Neutralization assays were performed on 256 PWH and 256 controls based on specimen availability at the timepoint of interest, having received two vaccines and known date of vaccination. There was a significant interaction between HIV status and previous COVID-19 infection status in median ID50. There were no differences in median ID50 for HIV+ vs. HIV-negative persons without past COVID-19 infection. For participants with past COVID-19 infection, median ICD50 was significantly higher in controls than in PWH for ancestral SARS-CoV-2 and Omicron variants, with a trend for the Delta variant in the same direction.

CONCLUSION

Vaccine-induced SARS-CoV-2 neutralization capacity was similar between PWH vs. HIV-negative persons without past COVID-19 infection, demonstrating favourable humoral-mediated immunogenicity. Both HIV+ and HIV-negative persons demonstrated hybrid immunity.

TRIAL REGISTRATION

clinicaltrials.gov NCT04894448.

Uncovering Spatiotemporal Dynamics of the Corticothalamic Network during Seizures

Objective

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human EEG recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci.

Methods

We analyzed ten patients (aged 2.7-28.1) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic coverage. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM).

Results

In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM.

Interpretation

It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network during seizures, and this knowledge could guide personalized neuromodulation treatment strategies.

Cross-sectional Characterization of SARS-CoV-2 Antibody Levels and Decay Rates Following Infection of Unvaccinated Elderly Individuals

Background

SARS-CoV-2 infections have disproportionally burdened elderly populations with excessive mortality. While several contributing factors exists, questions remain about the quality and duration of humoral antibody-mediated responses resulting from infections in unvaccinated elderly individuals.

Methods

Residual serum/plasma samples were collected from individuals undergoing routine SARS-CoV-2 polymerase chain reaction testing in a community laboratory in Canada. The samples were collected in 2020, before vaccines became available. IgG, IgA, and IgM antibodies against SARS-CoV-2 nucleocapsid, trimeric spike, and its receptor-binding domain were quantified via a high-throughput chemiluminescent enzyme-linked immunosorbent assay. Neutralization efficiency was also quantified through a surrogate high-throughput protein-based neutralization assay.

Results

This study analyzed SARS-CoV-2 antibody levels in a large cross-sectional cohort (N = 739), enriched for elderly individuals (median age, 82 years; 75% >65 years old), where 72% of samples tested positive for SARS-CoV-2 by polymerase chain reaction. The age group ≥90 years had higher levels of antibodies than that <65 years. Neutralization efficiency showed an age-dependent trend, where older persons had higher levels of neutralizing antibodies. Antibodies targeting the nucleocapsid had the fastest decline. IgG antibodies targeting the receptor-binding domain remained stable over time, potentially explaining the lack of neutralization decay observed in this cohort.

Conclusions

Despite older individuals having the highest levels of antibodies postinfection, they are the cohort in which antibody decay was the fastest. Until a better understanding of correlates of protection is acquired, along with the protective role of nonneutralizing antibodies, booster vaccinations remain important in this demographic.

Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data

BACKGROUND

The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA).

OBJECTIVE

The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA).

METHODS

Two different models were built to classify PRO scores; a random forest (RF) Classifier model that treated each week of observations independently when making weekly predictions of PRO scores, and a hidden Markov model (HMM) that additionally took correlations between successive weeks into account. Analyses compared model evaluation metrics for: 1) a binary task of distinguishing a normal PRO score from a severe PRO score, and 2) a multiclass task of classifying a PRO score state for a given week.

RESULTS

For both the binary and multiclass tasks, the HMM significantly (p < 0.05) outperformed the RF for most PRO scores, and the highest AUC, Pearson's Correlation coefficient, and Cohen's Kappa coefficient were 0.751, 0.458, and 0.450 respectively.

CONCLUSIONS

While further validation of our results and evaluation in a real-world setting yet remains, this study demonstrates the ability of physical activity tracker data to classify health status over time in patients with RA and enables the possibility of scheduling preventive clinical interventions as needed. If patient outcomes can be monitored in real time, there is potential to improve clinical care for patients with other chronic conditions.

CLINICALTRIAL

Multi-Parametric Radiomic Model to Predict 1p/19q Co-Deletion in Patients with IDH-1 Mutant Glioma: Added Value to the T2-FLAIR Mismatch Sign

PURPOSE

The T2-FLAIR mismatch sign has shown promise in determining IDH mutant 1p/19q non-co-deleted gliomas with a high specificity and modest sensitivity. To develop a multi-parametric radiomic model using MRI to predict 1p/19q co-deletion status in patients with newly diagnosed IDH1 mutant glioma and to perform a comparative analysis to T2-FLAIR mismatch sign+.

METHODS

In this retrospective study, patients with diagnosis of IDH1 mutant gliomas with known 1p/19q status who had preoperative MRI were included. T2-FLAIR mismatch was evaluated independently by two board-certified neuroradiologists. Texture features were extracted from glioma segmentation of FLAIR images. eXtremeGradient Boosting (XGboost) classifiers were used for model development. Leave-one-out-cross-validation (LOOCV) and external validation performances were reported for both the training and external validation sets.

RESULTS

A total of 103 patients were included for model development and 18 patients for external testing validation. The diagnostic performance (sensitivity/specificity/accuracy) in the determination of the 1p/19q co-deletion status was 59%/83%/67% (training) and 62.5%/70.0%/66.3% (testing) for the T2-FLAIR mismatch sign. This was significantly improved (p = 0.04) using the radiomics model to 77.9%/82.8%/80.3% (training) and 87.5%/89.9%/88.8% (testing), respectively. The addition of radiomics as a computer-assisted tool resulted in significant (p = 0.02) improvement in the performance of the neuroradiologist with 13 additional corrected cases in comparison to just using the T2-FLAIR mismatch sign.

CONCLUSION

The proposed radiomic model provides much needed sensitivity to the highly specific T2-FLAIR mismatch sign in the determination of the 1p/19q non-co-deletion status and improves the overall diagnostic performance of neuroradiologists when used as an assistive tool.

Abstract TP97: Automated Assessment Of DWI-FLAIR Mismatch To Predict Stroke-onset Time

Background and Purpose: DWI-FLAIR mismatch is used to determine thrombolytic eligibility in patients with acute ischemic stroke (AIS) when time-to-stroke symptom (TSS) is unknown. Advances in artificial intelligence and machine learning (ML) techniques have shown promising results in automated assessment of TSS. We aimed to use the e-Stroke software (Brainomix, Oxford, UK) to automatically classify DWI-FLAIR mismatch in a cohort of patients with AIS and in a comparative analysis with an expert neuroradiologist.

Methods: In this retrospective study, consecutive patients with AIS who had pretreatment MRI, and known TSS were included. DWI-FLAIR mismatch was evaluated by an expert neuroradiologist blinded to TSS. e-Stroke software, which uses a combination of statistical methods and ML classification techniques was used to automatically classify DWI-FLAIR status. TSS was dichotomized using a 4.5 hr cutoff to assess the diagnostic performance of the radiologist vs. e-Stroke software.

Results: Thus far 113 patients are included, 53 female, age (mean ± SD): 68.9 ± 17. TSS was 371±249 min (mean ± SD) and the infarct volume was 16.4±26.5 ml (mean ± SD). A total of 60 patients had TSS > 4.5 hrs while 53 had TSS < 4.5 hrs. Diagnostic performance (sensitivity/specificity/accuracy in %) for determination of TSS using DWI-FLAIR mismatch was 75/58.5/66.7 for the radiologist and 43/85/64 for e-Stroke software; without statistical difference (AUC: 0.66 for radiologist, 0.64 for e-Stroke; Delong test, p= 0.59). Subgroup analysis of infarctions of at least 1mL or higher, improved the diagnostic performance for both radiologist (83.8/59.4/71.6) and e-Stroke software (66.7/75.0/71.0), without statistical difference (AUC: 0.71 for radiologist and 0.71 for e-Stroke; Delong test, p= 0.96).

Conclusions: Results show that fully automated quantitative approach for DWI-FLAIR mismatch provides similar diagnostic accuracies to expert neuroradiologist in determination of TSS.

Abstract WP20: Patterns Of Alert And Management Of Cerebral Aneurysms Using An Incidental Aneurysm Alert System

Introduction: Incidentally discovered cerebral aneurysms are increasingly common as patients are more frequently imaged. To aid in this management, we developed an aneurysm alert system. Here we describe the effectiveness and outcomes of our Incidental Aneurysm Alert System (IAAS).

Methods: IAAS received MRA and CTA reports from our Radiology department. Reports were parsed using natural language processing to identify ‘aneurysm’, automatically generating alerts for the interventional neuroradiologists. Background demographics, referral patterns, risk factors and management were then assessed.

Results: From March to December 2020, 145 consecutive reports were reviewed. A 87% cerebral aneurysm detection accuracy rate resulted after excluding duplicates and non-vascular lesions, resulting in 117 unique cases. Median age was 65 and 65% were female. Most frequent races were 53% non-Hispanic White, 19% other, 9% Asian, 6% Black; 26% were of Hispanic ethnicity. The most common indication was acute stroke (29%). Of the detected aneurysms, 49% resulted in consultation with an interventionalist. Neurology was the most common referring specialty (37%). Of those referred, 49% underwent diagnostic and/or therapeutic angiography. Sixty eight percent who underwent cerebral angiography were intervened upon immediately or within 2 years of discovery. Seven percent were ruptured on discovery. Aneurysms were most frequently treated with flow diversion (37%), coiling (37%), and clipping (16%).Mean PHASES score of referred patients was 4.3, conferring 0.9-1.3% 5-year rupture risk. Asians and Hispanics had higher PHASES scores on presentation of 6.1 (1.7% 5-year rupture risk) and 5.2 (1.3% 5-year rupture risk) respectively, compared to Non-Hispanic Caucasians of 3.8 (0.9% 5-year rupture risk). For Hispanics, mean age was 55 and mean aneurysm size 9.8 mm as compared to 66 and 5.6 mm in non-Hispanic Caucasians. There were no significant differences in aneurysm risk factors.

Conclusions: IAAS is an effective alerting system. Hispanics were younger with larger aneurysms on detection. IAAS may have potential value in connecting general physicians with cerebrovascular specialists, improving the management of incidentally discovered cerebral aneurysms.

Fluorescence decay enhancement and FRET inhibition in self-assembled hybrid gold CdSe/CdS/CdZnS colloidal nanocrystal supraparticles

We report on the synthesis of hybrid light emitting particles with a diameter ranging between 100 and 500 nm, consisting in a compact semiconductor CdSe/CdS/CdZnS nanocrystal aggregate encapsulated by a controlled nanometric size silica and gold layers. We first characterize the Purcell decay rate enhancement corresponding to the addition of the gold nanoshell as a function of the particle size and find a good agreement with the predictions of numerical simulations. Then, we show that the contribution corresponding to Förster resonance energy transfer is inhibited.

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning

BACKGROUND

Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine noncontrast computed tomography (NCCT).

OBJECTIVE

We used an ML-trained algorithm to quantify ischemic core volume on NCCT in a comparative analysis to pretreatment magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in patients with AIS.

METHODS

Patients with AIS who had both pretreatment NCCT and MRI were enrolled. An automatic segmentation ML approach was applied using Brainomix software (Oxford, UK) to segment the ischemic voxels and calculate ischemic core volume on NCCT. Ischemic core volume was also calculated on baseline MRI DWI. Comparative analysis was performed using Bland-Altman plots and Pearson correlation.

RESULTS

A total of 72 patients were included. The time-to-stroke onset time was 134.2/89.5 minutes (mean/median). The time difference between NCCT and MRI was 64.8/44.5 minutes (mean/median). In patients who presented within 1 hour from stroke onset, the ischemic core volumes were significantly (p  =  0.005) underestimated by ML-NCCT. In patients presented beyond 1 hour, the ML-NCCT estimated ischemic core volumes approximated those obtained by MRI-DWI and with significant correlation (r  =  0.56, p < 0.001).

CONCLUSION

The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.

Cohort profile: top the Spread Ottawa (SSO)-a community-based prospective cohort study on antibody responses, antibody neutralisation efficiency and cellular immunity to SARS-CoV-2 infection and vaccination

PURPOSE

To investigate the robustness and longevity of SARS-CoV-2 immune responses conferred by natural infection and vaccination among priority populations such as immunocompromised individuals and people with post-acute sequelae of COVID-19 in a prospective cohort study (Stop the Spread Ottawa-SSO) in adults living in the Ottawa region. In this paper, we describe the study design, ongoing data collection and baseline characteristics of participants.

PARTICIPANTS

Since October 2020, participants who tested positive for COVID-19 (convalescents) or at high risk of exposure to the virus (under surveillance) have provided monthly blood and saliva samples over a 10-month period. As of 2 November 2021, 1026 adults had completed the baseline survey and 976 had attended baseline bloodwork. 300 participants will continue to provide bimonthly blood samples for 24 additional months (ie, total follow-up of 34 months).

FINDINGS TO DATE

The median age of the baseline sample was 44 (IQR 23, range: 18-79) and just over two-thirds (n=688; 67.1%) were female. 255 participants (24.9%) had a history of COVID-19 infection confirmed by PCR and/or serology. Over 600 participants (60.0%) work in high-risk occupations (eg, healthcare, teaching and transportation). 108 participants (10.5%) reported immunocompromising conditions or treatments at baseline (eg, cancer, HIV, other immune deficiency, and/or use of immunosuppressants).

FUTURE PLANS

SSO continues to yield rich research potential, given the collection of pre-vaccine baseline data and samples from the majority of participants, recruitment of diverse subgroups of interest, and a high level of participant retention and compliance with monthly sampling. The 24-month study extension will maximise opportunities to track SARS-CoV-2 immunity and vaccine efficacy, detect and characterise emerging variants, and compare subgroup humoral and cellular response robustness and persistence.

Comparative performance data for multiplex SARS-CoV-2 serological assays from a large panel of dried blood spot specimens

The extent of the COVID-19 pandemic will be better understood through serosurveys and SARS-CoV-2 antibody testing. Dried blood spot (DBS) samples will play a central role in large scale serosurveillance by simplifying biological specimen collection and transportation, especially in Canada. Direct comparative performance data on multiplex SARS-CoV-2 assays resulting from identical DBS samples are currently lacking. In our study, we aimed to provide performance data for the BioPlex 2200 SARS-CoV-2 IgG (Bio-Rad), V-PLEX SARS-CoV-2 Panel 2 IgG (MSD), and Elecsys Anti-SARS-CoV-2 (Roche) commercial assays, as well as for two highly scalable in-house assays (University of Ottawa and Mount Sinai Hospital protocols) to assess their suitability for DBS-based SARS-CoV-2 DBS serosurveillance. These assays were evaluated against identical panels of DBS samples collected from convalescent COVID-19 patients (n = 97) and individuals undergoing routine sexually transmitted and bloodborne infection (STBBI) testing prior to the COVID-19 pandemic (n = 90). Our findings suggest that several assays are suitable for serosurveillance (sensitivity >97% and specificity >98%). In contrast to other reports, we did not observe an improvement in performance using multiple antigen consensus-based rules to establish overall seropositivity. This may be due to our DBS panel which consisted of samples collected from convalescent COVID-19 patients with significant anti-spike, -receptor binding domain (RBD), and -nucleocapsid antibody titers. This study demonstrates that biological specimens collected as DBS coupled with one of several readily available assays are useful for large-scale COVID-19 serosurveillance.

Antibody Seronegativity in COVID-19 RT-PCR-Positive Children

This substudy of a prospective case-ascertained household transmission study investigated severe acute respiratory syndrome coronavirus 2 reverse transcription polymerase chain reaction-positive individuals without antibody development and factors associated with nonseroconversion. Approximately 1 of 8 individuals with coronavirus disease 2019 did not seroconvert. Children, particularly the youngest, were approximately half as likely to seroconvert compared with adults. Apart from the absence of fever/chills, individual symptoms did not strongly predict nonseroconversion.

Prevalence of SARS-CoV-2 infection among obstetric patients in Ottawa, Canada: a descriptive study

BACKGROUND

There is limited information on the prevalence of SARS-CoV-2 infection in obstetric settings in Canada, beyond the first wave of the COVID-19 pandemic (February to June 2020). We sought to describe the prevalence of SARS-CoV-2 infection in pregnant people admitted to triage units at a tertiary care hospital in Ottawa, Canada.

METHODS

We conducted a descriptive study of pregnant people admitted to obstetric triage assessment units at The Ottawa Hospital between Oct. 19 and Nov. 27, 2020 (second local wave of the COVID-19 pandemic). Participants underwent SARS-CoV-2 polymerase chain reaction (PCR) (via naso- or oropharyngeal swabs) and serology testing upon admission. We excluded individuals younger than 18 years, those who did not speak English or French, those who enrolled in conflicting studies, those admitted for pregnancy termination and those triaged between 11:31 pm and 7:29 am. Swab and serology samples were analyzed using digital droplet PCR and enzyme-linked immunosorbent assays, respectively. We defined SARS-CoV-2 seropositivity as a positive result for immunoglobulin (Ig) G, either alone or in combination with IgM or IgA.

RESULTS

Of the 632 eligible patients, 363 (57.4%) consented to participation and 362 collectively provided 284 swab and 352 blood samples eligible for analysis. Common reasons for declining participation included feeling overwhelmed or anxious, being worried about repercussions of testing, pain or discomfort with testing or disinterest in research. Participants were mostly multiparous (53.9%) and in their third trimester upon admission (88.4%). In all, 18 (4.9%) participants had evidence of SARS-CoV-2 exposure; 2 (0.7%) of 284 were positive for SARS-CoV-2 by PCR and 16 (4.5%) of 352 were positive for IgG antibodies to SARS-CoV-2.

INTERPRETATION

During the second local wave of the COVID-19 pandemic, the prevalence of active SARS-CoV-2 infection among obstetric patients in Ottawa was 0.7% and seroprevalence was 4.5%. Our low participation rate highlights the need for improvements in patient education and public health messaging on the benefits of SARS-CoV-2 testing programs.

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

Seropositivity and risk factors for SARS-CoV-2 infection in a South Asian community in Ontario: a cross-sectional analysis of a prospective cohort study

BACKGROUND

Early in the COVID-19 pandemic, the South Asian community in the Greater Toronto Area (GTA) was identified as having risk factors for exposure and specific barriers to accessing testing and reliable health information, rendering them particularly vulnerable to SARS-CoV-2 infection. We sought to investigate the burden of SARS-CoV-2 infection among South Asian people in the GTA, and to characterize the demographic characteristics, risk perceptions and trusted sources of health information in this group.

METHODS

We conducted a cross-sectional analysis from the baseline assessment of participants in a prospective cohort study. Participants from the GTA were enrolled from Apr. 14 to July 28, 2021. Seropositivity for antispike and antinucleocapsid antibodies was determined from dried blood spots, and estimates of seropositivity were age and sex standardized to the South Asian population in Ontario. Demographic characteristics, risk perceptions and sources of COVID-19 information were collected via questionnaire and reported descriptively.

RESULTS

Among the 916 South Asian participants enrolled (mean age 41 yr), the age- and sex-standardized seropositivity was 23.6% (95% confidence interval 20.8%-26.4%). Of the 693 respondents to the questionnaire, 228 (32.9%) identified as essential workers, and 125 (19.1%) reported living in a multigenerational household. A total of 288 (49.4%) perceived that they were at high COVID-19 risk owing to their geographic location, and 149 (34.3%) owing to their type of employment. The top 3 most trusted sources of information related to COVID-19 included health care providers and public health, traditional media sources and social media.

INTERPRETATION

By the third wave of the COVID-19 pandemic, about one-quarter of a sample of South Asian individuals in Ontario had serologic evidence of prior SARS-CoV-2 infection. Insight into factors that put certain populations at risk can help future pandemic planning and disease control efforts.

POS1412 FIRSTS RESULTS OF THE PRAISE STUDY (PATIENT-REPORTED AUTOIMMUNITY SECONDARY TO CANCER IMMUNOTHERAPY): MULTICENTRIC PROSPECTIVE COHORT STUDY ON AUTOIMMUNE DISEASES SECONDARY TO CANCER IMMUNOTHÉRAPY

Background

In cancer immunotherapy, T-lymphocyte activation can lead to secondary autoimmune diseases named OASI for Opportunistic Autoimmunity Secondary to cancer Immunotherapy [1]. The epidemiology of OASI deserves to be further studied due to the unadapted reporting of clinical trials and the lack of prospective studies. Moreover, literature focuses on the most severe OASI and/or on specific OASI (myocarditis, colitis, arthritis).

Objectives

Our goal was to determine incidence, severity of all grade OASI using a multicentric prospective patient cohort starting treatment with cancer immunotherapy.

Methods

We present a multicentric, prospective, observational, longitudinal, real life, French e-cohort. 900 patients treated with ipilimumumab and/or nivolumab will be included. Data is collected from the patient and the oncologist at inclusion, then patients report directly any symptom that could be suggestive of OASI with the help of monthly digital questionaries. In case an OASI is suspected, further confirmation is made with the practician in charge and by a paired analysis with the Système National De Santé (SNDS), the French health insurance registry.

Results

On the 19/01/2022, 439 patients were included, 310 males (70.6%) and 129 females (29.4%). Mean age is 66 years old with a median follow up of 192 days. 354 patients (80.6%) are treated with Nivolumab alone, 7 (1.6%) with Ipilimumab alone and 76 (17.8 %) with combined Nivolumab + Ipilimumab. 136 patients (31.6%) are treated for a non-small cell lung carcinoma, 107 patients (24.9%) for a clear cell renal carcinoma, 91 patients (21.2%) for a skin melanoma, 49 patients (11.4%) for a head or neck epidermoid carcinoma, 24 patients (5.6%) for another lung cancer sub-type, and 32 patients (5.3%) for another histological cancer type. The mean follow-up is 294 days (+/- 192). 83 patients (18.9%) died since the beginning of the follow up.

47 patients (10.7%) developed 63 OASI. The mean delay between the beginning of cancer immunotherapy and the OASI is 134.7 days (+/- 103.4).

Approximately, one third of the OASI were musculoskeletal diseases. The OASI included polymyalgia rheumatica (3 patients), psoriatic arthritis (1 patient), polyarthritis (1 patient) systemic lupus (1 patient), arthralgias and myalgias (8 patients), colitis (11 patients), dysthyroïditis (6 patients), hepatitis (4 patients), nephritis (3 patients), pneumonitis (2 patients), hypophysitis (2 patients), adrenal insufficiency (4 patients), myocarditis (1 patient), hemophagocytic lympho-histiocytosis (1 patient), and other types of OASI (15 patients).

26 patients (55% of patients with OASI, 5,9% of all patients) had to stop cancer immunotherapy due to an OASI, one because of a rheumatic disease (systemic lupus). 52 patients were treated with corticosteroids, 1 patient with methotrexate (psoriatic arthritis), 3 patients with infliximab (colitis) and 1 patient with abatacept (myocarditis). 1 patient died after an OASI (colitis).

Conclusion

The first results of this prospective study, using an original patient-centered methodology, confirm the expected incidence of autoimmune events secondary to cancer immunotherapy and the role of rheumatologists in their therapeutic management.

References

[1]Kostine M, Chiche L, Lazaro E, et al. Opportunistic autoimmunity secondary to cancer immunotherapy (OASI): An emerging challenge. Rev Med Interne. 2017;38(8):513-525. doi:10.1016/j.revmed.2017.01.004

Acknowledgements

BMS funded the study (unrestricted grant) but had no role in study design, data collection, analysis or decision to publish.

Disclosure of Interests

Eden Sebbag: None declared, Nicolas Cloarec: None declared, Philippe Barthelemy: None declared, Nathanaël Sedmak: None declared, Naima Hamamouche Consultant of: Work for Sanoia Digital CRO, Hervé Servy Consultant of: Work for Sanoia Digital CRO, Guillaume Desjeux Consultant of: Work for Sanoia Digital CRO, Isabelle Monnet: None declared, Abeer Najem: None declared, Marc Porneuf: None declared, Laetitia-Shanna Rajpar: None declared, Jérôme Meunier: None declared, Tévy San: None declared, Laure Chauvenet: None declared, Ariane DARUT JOUVE: None declared, Sabrina FALKOWSKI: None declared, Claudia Rizzo: None declared, Noémie Litrowski: None declared, Anthony Canellas: None declared, Jean-François Paitel: None declared, Marc Pracht: None declared, Jacques Cadranel: None declared, Laurence Weiss: None declared, Christos Chouaid: None declared, Thomas Aparicio: None declared, Stephane Nancey: None declared, Cécile Arnold: None declared, Erik Sauleau: None declared, Jaqcues-Eric Gottenberg: None declared

Sex-based differences in remote monitoring of biometric, psychometric and biomarker indices in stable ischemic heart disease

BACKGROUND

Sex-based differences are crucial to consider in the formulation of a personalized treatment plan. We evaluated sex-based differences in adherence and remotely monitored biometric, psychometric, and biomarker data among patients with stable ischemic heart disease (IHD).

METHODS

The Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE-MACE) study evaluated patients with stable IHD over a 12-week period. We collected biometric and sleep data using remote patient monitoring via FitBit and psychometric data from Patient-Reported Outcomes Measurement Information System (PROMIS), Kansas City Cardiomyopathy (KCC) and Seattle Angina Questionnaire-7 (SAQ-7) questionnaires. Serum biomarker levels were collected at the baseline visit. We explored sex-based differences in demographics, adherence to study protocols, biometric data, sleep, psychometric data, and biomarker levels.

RESULTS

There were 198 patients enrolled, with mean age 65.5 ± 11 years (± Standard deviation, SD), and 60% were females. Females were less adherent to weekly collection of PROMIS, KCC and SAQ-7 physical limitations questionnaires (all p < 0.05), compared to males. There was no difference in biometric physical activity. There was a statistically significant (p < 0.05) difference in sleep duration between sexes, with females sleeping 6 min longer. However, females reported higher PROMIS sleep disturbance scores (p < 0.001) and poorer psychometric scores overall (p < 0.05). A higher proportion of males had clinically significant elevations of median N-terminal pro-brain natriuretic peptide (p = 0.005) and high-sensitivity cardiac troponin levels (p < 0.001) compared to females.

CONCLUSIONS

Among females and males with stable IHD, there are sex-based differences in remote monitoring behavior and data. Females are less adherent to psychometric data collection and report poorer psychometric and sleep quality scores than males. Elevated levels of biomarkers for MACE are more common in males. These findings may improve sex-specific understanding of IHD using remote patient monitoring.

A scalable serology solution for profiling humoral immune responses to SARS-CoV-2 infection and vaccination

Objectives

Antibody testing against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has been instrumental in detecting previous exposures and analyzing vaccine‐elicited immune responses. Here, we describe a scalable solution to detect and quantify SARS‐CoV‐2 antibodies, discriminate between natural infection‐ and vaccination‐induced responses, and assess antibody‐mediated inhibition of the spike‐angiotensin converting enzyme 2 (ACE2) interaction.

Methods

We developed methods and reagents to detect SARS‐CoV‐2 antibodies by enzyme‐linked immunosorbent assay (ELISA). The main assays focus on the parallel detection of immunoglobulin (Ig)Gs against the spike trimer, its receptor binding domain (RBD) and nucleocapsid (N). We automated a surrogate neutralisation (sn)ELISA that measures inhibition of ACE2‐spike or ‐RBD interactions by antibodies. The assays were calibrated to a World Health Organization reference standard.

Results

Our single‐point IgG‐based ELISAs accurately distinguished non‐infected and infected individuals. For seroprevalence assessment (in a non‐vaccinated cohort), classifying a sample as positive if antibodies were detected for ≥ 2 of the 3 antigens provided the highest specificity. In vaccinated cohorts, increases in anti‐spike and ‐RBD (but not ‐N) antibodies are observed. We present detailed protocols for serum/plasma or dried blood spots analysis performed manually and on automated platforms. The snELISA can be performed automatically at single points, increasing its scalability.

Conclusions

Measuring antibodies to three viral antigens and identify neutralising antibodies capable of disrupting spike‐ACE2 interactions in high‐throughput enables large‐scale analyses of humoral immune responses to SARS‐CoV‐2 infection and vaccination. The reagents are available to enable scaling up of standardised serological assays, permitting inter‐laboratory data comparison and aggregation.

Household transmission of SARS-CoV-2 from unvaccinated asymptomatic and symptomatic household members with confirmed SARS-CoV-2 infection: an antibody-surveillance study

BACKGROUND

Household transmission contributes to SARS-CoV-2 spread, but the role of children in transmission is unclear. We conducted a study that included symptomatic and asymptomatic children and adults exposed to SARS-CoV-2 in their households with the objective of determining how SARS-CoV-2 is transmitted within households.

METHODS

In this case-ascertained antibody-surveillance study, we enrolled households in Ottawa, Ontario, in which at least 1 household member had tested positive for SARS-CoV-2 on reverse transcription polymerase chain reaction testing. The enrolment period was September 2020 to March 2021. Potentially eligible participants were identified if they had tested positive for SARS-CoV-2 at an academic emergency department or affiliated testing centre; people who learned about the study through the media could also self-identify for participation. At least 2 participants were required for a household to be eligible for study participation, and at least 1 enrolled participant per household had to be a child (age < 18 yr). Enzyme-linked immunosorbent assays were used to evaluate SARS-CoV-2-specific IgA, IgM and IgG against the spike-trimer and nucleocapsid protein. The primary outcome was household secondary attack rate, defined as the proportion of household contacts positive for SARS-CoV-2 antibody among the total number of household contacts participating in the study. We performed descriptive statistics at both the individual and household levels. To estimate and compare outcomes between patient subgroups, and to examine predictors of household transmission, we fitted a series of multivariable logistic regression with robust standard errors to account for clustering of individuals within households.

RESULTS

We enrolled 695 participants from 180 households: 180 index participants (74 children, 106 adults) and 515 of their household contacts (266 children, 249 adults). A total of 487 household contacts (94.6%) (246 children, 241 adults) had SARS-CoV-2 antibody testing, of whom 239 had a positive result (secondary attack rate 49.1%, 95% confidence interval [CI] 42.9%-55.3%). Eighty-eight (36.8%, 95% CI 29.3%-43.2%) of the 239 were asymptomatic; asymptomatic rates were similar for children (51/130 [39.2%, 95% CI 30.7%-48.5%]) and adults (37/115 [32.2%, 95% CI 24.2%-41.4%]) (odds ratio [OR] 1.3, 95% CI 0.8-2.1). Adults were more likely than children to transmit SARS-CoV-2 (OR 2.2, 95% CI 1.3-3.6). The odds of transmission from asymptomatic (OR 0.6, 95% CI 0.2-1.4) versus symptomatic (OR 0.9, 95% CI 0.6-1.4) index participants to household contacts was uncertain. Predictors of household transmission included household density (number of people per bedroom), relationship to index participant and number of cases in the household.

INTERPRETATION

The rate of SARS-CoV-2 transmission within households was nearly 50% during the study period, and children were an important source of spread. The findings suggest that children are an important driver of the COVID-19 pandemic; this should inform public health policy.

Real-world serological responses to extended-interval and heterologous COVID-19 mRNA vaccination in frail, older people (UNCoVER): an interim report from a prospective observational cohort study

BACKGROUND

The use of COVID-19 vaccines has been prioritised to protect the most vulnerable-notably, older people. Because of fluctuations in vaccine availability, strategies such as delayed second dose and heterologous prime-boost have been used. However, the effectiveness of these strategies in frail, older people are unknown. We aimed to assess the antigenicity of mRNA-based COVID-19 vaccines in frail, older people in a real-world setting, with a rationed interval dosing of 16 weeks between the prime and boost doses.

METHODS

This prospective observational cohort study was done across 12 long-term care facilities of the Montréal Centre-Sud - Integrated University Health and Social Services Centre in Montréal, Québec, Canada. Under a rationing strategy mandated by the provincial government, adults aged 65 years and older residing in long-term care facilities in Québec, Canada, with or without previously documented SARS-CoV-2 infection, were administered homologous or heterologous mRNA vaccines, with an extended 16-week interval between doses. All older residents in participating long-term care facilities who received two vaccine doses were eligible for inclusion in this study. Participants were enrolled from Dec 31, 2020, to Feb 16, 2021, and data were collected up to June 9, 2021. Clinical data and blood samples were serially collected from participants at the following timepoints: at baseline, before the first dose; 4 weeks after the first dose; 6-10 weeks after the first dose; 16 weeks after the first dose, up to 2 days before administration of the second dose; and 4 weeks after the second dose. Sera were tested for SARS-CoV-2-specific IgG antibodies (to the trimeric spike protein, the receptor-binding domain [RBD] of the spike protein, and the nucleocapsid protein) by automated chemiluminescent ELISA. Two cohorts were used in this study: a discovery cohort, for which blood samples were collected before administration of the first vaccine dose and longitudinally thereafter; and a confirmatory cohort, for which blood samples were only collected from 4 weeks after the prime dose. Analyses were done in the discovery cohort, with validation in the confirmatory cohort, when applicable.

FINDINGS

The total study sample consisted of 185 participants. 65 participants received two doses of mRNA-1273 (Spikevax; Moderna), 36 received two doses of BNT162b2 (Comirnaty; Pfizer-BioNTech), and 84 received mRNA-1273 followed by BNT162b2. In the discovery cohort, after a significant increase in anti-RBD and anti-spike IgG concentrations 4 weeks after the prime dose (from 4·86 log binding antibody units [BAU]/mL to 8·53 log BAU/mL for anti-RBD IgG and from 5·21 log BAU/mL to 8·05 log BAU/mL for anti-spike IgG), there was a significant decline in anti-RBD and anti-spike IgG concentrations until the boost dose (7·10 log BAU/mL for anti-RBD IgG and 7·60 log BAU/mL for anti-spike IgG), followed by an increase 4 weeks later for both vaccines (9·58 log BAU/mL for anti-RBD IgG and 9·23 log BAU/mL for anti-spike IgG). SARS-CoV-2-naive individuals showed lower antibody responses than previously infected individuals at all timepoints tested up to 16 weeks after the prime dose, but achieved similar antibody responses to previously infected participants by 4 weeks after the second dose. Individuals primed with the BNT162b2 vaccine showed a larger decrease in mean anti-RBD and anti-spike IgG concentrations with a 16-week interval between doses (from 8·12 log BAU/mL to 4·25 log BAU/mL for anti-RBD IgG responses and from 8·18 log BAU/mL to 6·66 log BAU/mL for anti-spike IgG responses) than did those who received the mRNA-1273 vaccine (two doses of mRNA-1273: from 8·06 log BAU/mL to 7·49 log BAU/mL for anti-RBD IgG responses and from 6·82 log BAU/mL to 7·56 log BAU/mL for anti-spike IgG responses; mRNA-1273 followed by BNT162b2: from 8·83 log BAU/mL to 7·95 log BAU/mL for anti-RBD IgG responses and from 8·50 log BAU/mL to 7·97 log BAU/mL for anti-spike IgG responses). No differences in antibody responses 4 weeks after the second dose were noted between the two vaccines, in either homologous or heterologous combinations.

INTERPRETATION

Interim results of this ongoing longitudinal study show that among frail, older people, previous SARS-CoV-2 infection and the type of mRNA vaccine influenced antibody responses when used with a 16-week interval between doses. In these cohorts of frail, older individuals with a similar age and comorbidity distribution, we found that serological responses were similar and clinically equivalent between the discovery and confirmatory cohorts. Homologous and heterologous use of mRNA vaccines was not associated with significant differences in antibody responses 4 weeks following the second dose, supporting their interchangeability.

FUNDING

Public Health Agency of Canada, Vaccine Surveillance Reference Group; and the COVID-19 Immunity Task Force.

TRANSLATION

For the French translation of the abstract see Supplementary Materials section.

Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis

Background

Current qualitative literature about the experiences of women dealing with urinary tract infections (UTIs) is limited to patients recruited from tertiary centers and medical clinics. However, traditional focus groups and interviews may limit what patients share. Using digital ethnography, we analyzed free-range conversations of an online community.

Objective

This study aimed to investigate and characterize the patient perspectives of women dealing with UTIs using digital ethnography.

Methods

A data-mining service was used to identify online posts. A thematic analysis was conducted on a subset of the identified posts. Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. Each identified topic was generated as a discrete distribution over the words in the collection, which can be thought of as a word cloud. We also performed a thematic analysis of the word cloud topic model results.

Results

A total of 83,589 posts by 53,460 users from 859 websites were identified. Our hand-coding inductive analysis yielded the following 7 themes: quality-of-life impact, knowledge acquisition, support of the online community, health care utilization, risk factors and prevention, antibiotic treatment, and alternative therapies. Using the LDA topic model method, 105 themes were identified and consolidated into 9 categories. Of the LDA-derived themes, 25.7% (27/105) were related to online community support, and 22% (23/105) focused on UTI risk factors and prevention strategies.

Conclusions

Our large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women’s UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way.

Forensisch-medizinische Untersuchungen von Tatverdächtigen. Eine Analyse von 270 Gutachten aus den Jahren 2006 bis 2018

Hintergrund

Zu den Aufgaben in der rechtsmedizinischen Praxis gehören zunehmend forensisch-medizinische Untersuchungen von Lebenden. Im Gegensatz zu Studien über Gewaltopfer findet sich in der Fachliteratur allerdings ein erhebliches Defizit an Ergebnissen über systematische rechtsmedizinische Untersuchungen von Tatverdächtigen.

Fragestellung

Welche relevanten Daten können aus einer retrospektiven Analyse von forensisch-medizinischen Untersuchungen von Tatverdächtigen erhoben und welche Rückschlüsse für die rechtsmedizinische Praxis gezogen werden?

Material und Methode

Es wurden insgesamt 270 Gutachten nach forensisch-medizinischen Untersuchungen von Tatverdächtigen aus dem Einzugsgebiet des Instituts für Rechtsmedizin der Universitätsmedizin Rostock der Jahre 2006 bis 2018 nach vorab definierten Kriterien ausgewertet.

Ergebnisse

Die vorgeworfenen Straftaten waren am häufigsten Körperverletzungen (n = 88 = 30,7 %), gefolgt von vorsätzlichen Tötungen (n = 63 = 22,0 %) und Sexualdelikten (n = 49 = 17,1 %). Von den begutachteten Personen waren 236 (87,4 %) männlich und 34 (12,6 %) weiblich. Die Mehrzahl der Tatverdächtigen (n = 175 = 65,5 %) war in einem Lebensalter von 18 bis 40 Jahren.

Im Hinblick auf die Aussage der rechtsmedizinischen Ergebnisse in Bezug auf den vorgeworfenen Straftatbestand wurden 126 (46,7 %) Gutachten als für den Tatverdächtigen belastend, 13 (4,8 %) als entlastend und 131 (48,5 %) als frei von Be- oder Entlastungsaussagen eingestuft.

Zu den 270 Gutachten über Tatverdächtige gab es 209 (77,4 %) korrespondierende Opferuntersuchungen. Von diesem Teilkollektiv mit Täter-Opfer-Begutachtungen wurden in 193 Fällen (92,3 %) Tatverdächtige und Opfer von demselben Gutachter untersucht.

Schlussfolgerungen

Für die Rekonstruktion eines Tatgeschehens sind rechtsmedizinische Untersuchungen des Opfers und des Tatverdächtigen wertvoller als die nicht selten beobachtete Untersuchung der geschädigten Person allein. Befunde mit belastenden Tendenzen für den Tatverdächtigen werden häufiger festgestellt als solche, die zu einer Entlastung des Beschuldigten führen. Da es in der Fachliteratur im Vergleich zu den Opfern von Gewalttaten ein Defizit an Ergebnissen über systematische forensisch-medizinische Untersuchungen von Tatverdächtigen gibt, sollten weitere Studien folgen.

High resolution histopathology image generation and segmentation through adversarial training

Semantic segmentation of histopathology images can be a vital aspect of computer-aided diagnosis, and deep learning models have been effectively applied to this task with varying levels of success. However, their impact has been limited due to the small size of fully annotated datasets. Data augmentation is one avenue to address this limitation. Generative Adversarial Networks (GANs) have shown promise in this respect, but previous work has focused mostly on classification tasks applied to MR and CT images, both of which have lower resolution and scale than histopathology images. There is limited research that applies GANs as a data augmentation approach for large-scale image semantic segmentation, which requires high-quality image-mask pairs. In this work, we propose a multi-scale conditional GAN for high-resolution, large-scale histopathology image generation and segmentation. Our model consists of a pyramid of GAN structures, each responsible for generating and segmenting images at a different scale. Using semantic masks, the generative component of our model is able to synthesize histopathology images that are visually realistic. We demonstrate that these synthesized images along with their masks can be used to boost segmentation performance, especially in the semi-supervised scenario.

Visual Impairment and Functional Classification in Children with Cerebral Palsy

BACKGROUND

Cerebral palsy (CP) is the most common motor impairment in childhood and often accompanied by a broad spectrum of comorbidities. Data are sparse concerning visual impairment (VI) and functional classification among CP children.

OBJECTIVE

The objective of this study was to analyze the prevalence of VI among children with CP and to investigate a possible association between VI and Gross Motor Function Classification System (GMFCS) and the Bimanual Fine Motor Function (BFMF).

METHODS

In this hospital-based study, records of 200 children with CP aged 2 to 17 years were reviewed.

RESULTS

Overall, VI was found in 59.5% of children with CP. Prevalence of VI was higher when compared with non-CP children. A correlation between GMFCS as well as BFMF and severity of VI was found. Children with severe CP were at greater risk for severe VI, especially cerebral VI compared with children with mild CP.

CONCLUSION

VI is a significant problem in children with CP and is correlated with motor function. Children with CP should undergo detailed ophthalmologic and orthoptic assessment to enable early intervention.

10-Year Clinical Comparative Study of Ceramic and Composite Veneered Metal Crowns

The rejection of composite veneerings in fixed partial dentures is primarily caused by the inadequacy of the bonds between the metal framework and the composite veneering. The development of improved veneering composites necessitates an investigation of their clinical suitability compared with ceramic materials. Nineteen patients with at least two suitable, adjacent natural teeth for crowning were treated with 64 high noble alloy crowns. The adjacent crowns were veneered with ceramic (IPS inline) and composite materials (SR Adoro). Seven follow-up examinations were carried out over a period of 10 years. The crowns were investigated for mechanical defects, periodontal parameters, and discolorations. The survival rates of the ceramic veneered metal crowns (CeMCs) and composite veneered metal crowns (CoMCs) at the 10-year follow-up were 87.1 and 87.9%, respectively. The success rates of the crowns after 10 years were 83.9% for CeMCs and 51.5% for CoMCs (log-rank test, p = 0.009). No significant differences between the groups were found in the periodontal parameters (Kruskal-Wallis one-way analysis of variance, ANOVA p ⟩ 0.05). After 10 years, discoloration patterns of the two materials differed significantly (Mann-Whitney-U-test, p = 0.017). Thus, despite the improvements associated with CoMCs, CeMCs remain the gold standard for veneered metal crowns.

A Machine Learning Approach to Predict Acute Ischemic Stroke Thrombectomy Reperfusion using Discriminative MR Image Features

Mechanical thrombectomy (MTB) is one of the two standard treatment options for Acute Ischemic Stroke (AIS) patients. Current clinical guidelines instruct the use of pretreatment imaging to characterize a patient's cerebrovascular flow, as there are many factors that may underlie a patient's successful response to treatment. There is a critical need to leverage pretreatment imaging, taken at admission, to guide potential treatment avenues in an automated fashion. The aim of this study is to develop and validate a fully automated machine learning algorithm to predict the final modified thrombolysis in cerebral infarction (mTICI) score following MTB. A total 321 radiomics features were computed from segmented pretreatment MRI scans for 141 patients. Successful recanalization was defined as mTICI score >= 2c. Different feature selection methods and classification models were examined in this study. Our best performance model achieved 74.42±2.52% AUC, 75.56±4.44% sensitivity, and 76.75±4.55% specificity, showing a good prediction of reperfusion quality using pretreatment MRI. Results suggest that MR images can be informative to predicting patient response to MTB, and further validation with a larger cohort can determine the clinical utility.

Female Lower Urinary Tract Symptom Prevention and Treatment Strategies on Social Media: Mixed Correlation With Evidence

OBJECTIVE

To evaluate the level of evidence behind recommendations on social media for disease prevention in five lower urinary tract symptoms.

MATERIALS AND METHODS

We conducted a digital analysis of anonymous online posts on social media sites collected by a social media data mining service. One thousand posts about pelvic organ prolapse, stress urinary incontinence, overactive bladder, urinary tract infection, and interstitial cystitis/bladder pain syndrome were randomly selected. We analyzed these posts for recommendations regarding the prevention and treatment of these diseases, which were then compared to recommendations in available clinical guidelines and assessed for level of evidence.

RESULTS

A total of 158 of 1000 posts contained 239 prevention strategies. For pelvic organ prolapse, there were 41 strategies identified, 25 (61%) of which had no evidence. For urinary tract infection 14 of 58 (29%) had no evidence, including recommendations for dietary modifications and urinary alkalization. For overactive bladder 8 of 28 (29%) had level 4 or no evidence. For stress urinary incontinence, 12 of 34 (36%) of prevention strategies had no evidence, such as laser rejuvenation and bladder training. Interstitial cystitis had the highest number of prevention strategies, and most were low or nonevidence based (70/79, 89%).

CONCLUSION

Prevention and treatment strategies are common in online discussions of pelvic floor disorders, but at least one third of these recommendations have no evidential support. There is a role for further online education and social media engagement by health care specialists to promote evidence-based practices.

Using Digital Ethnography to Understand the Experience of Women With Pelvic Organ Prolapse

OBJECTIVE

To characterize the decision-making process and illness experience of women with pelvic organ prolapse (POP) using large-scale social media analysis.

METHODS

Digital ethnographic analysis of online posts identified through data mining was performed. Grounded theory methodology was applied to 200 posts via traditional hand coding. To supplement our qualitative approach, we applied a Latent Dirichlet Allocation probabilistic topic modeling process to review the entire data set of identified posts to ensure thematic saturation.

RESULTS

There were 3451 posts by 2088 unique users from 117 websites worldwide that were identified via social media data mining. We found that the anonymity of online forums allowed for information and support exchange among women with POP. Our analysis revealed that the exchange of online information aids in the decision-making process and, in some instances, appears to be the primary source of information. There was confusion about the anatomical and surgical complexities of prolapse. Our study also identified misconceptions, perceived risk factors, prevention methods, and management recommendations that were discussed online.

CONCLUSIONS

This large-scale online community-based analysis demonstrated the utility of social media to better understand women's experiences with POP. Thematic findings highlighted essential concerns and challenges involved in the surgical decision-making process and the understating of the anatomical complexity of sector defects, specifically to cystocele, rectocele, State specific defects.