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Record W4294958957 · doi:10.1136/bmjopen-2022-062187

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

2022· article· en· W4294958957 on OpenAlexafffundabout
Erin Collins, Yannick Galipeau, Corey Arnold, Cameron Jackson Bosveld, Aliisa Heiskanen, Alexa Keeshan, Kiran Nakka, Khatereh Shir-Mohammadi, Frédéric St-Denis Bissonnette, Laura Tamblyn, Agatha Vranjkovic, Leah C Wood, Ronald A. Booth, C. Arianne Buchan, Angela M. Crawley, Julian Little, Michaeline McGuinty, Raphael Saginur, Marc‐André Langlois, Curtis Cooper

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsResponse Biomedical (Canada)Canadian Electricity AssociationOttawa HospitalInstitute of Infection and ImmunityUniversity of Ottawa
FundersNational Research Council CanadaOttawa Hospital Research InstituteCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsMedicineAntibodyProspective cohort studyCohortImmunologyImmunityNeutralizationCohort studyVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)Immune systemInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.833

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.437
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2022
Admission routes3
Has abstractyes

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