Observational study of SARS-CoV-2 antibody immune response in a cohort of patients at a North Suburban Chicago, Illinois, in a physician’s practice
Bibliographic record
Abstract
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. The application of point of care serological testing can help determine past infection and assist healthcare workers assess patient risk. Method: An observational study of 114 subjects in North Suburban Chicago, Illinois, was performed using the Clungene® lateral flow immunoassay (LFI). Patients’ PCR test results and clinical symptoms were used to compare the seroconversion rate of this patient population with the surrounding community. Results: Excluding 1 aberrant result, there was 100% positive agreement (10) between PCR and antibody (IgG or IgM) test results. There were 7 patients who did not have a prior PCR test who were positive for IgG; 5 of the 7 had clinical symptoms consistent with possible exposure and 2 were asymptomatic. There was 1 person with a suspected exposure to an infected person who was IgM positive. Ninety-five asymptomatic patients were seronegative. The overall rate of 15.9% seroconversion (IgG or IgM) is consistent with other community-based testing results in the North Suburban Chicago, Illinois area. Conclusion: Rapid screening tests to identify antibody positive patients recovered from coronavirus disease-2019 can be a useful tool for healthcare professionals to determine or confirm past infection. Statement of novelty: Limited data is available on the use of point of care serological testing to assist healthcare professionals with the assessment of their patient population regarding past SARS-CoV-2 infectivity and seroconversion. The present study successfully investigated the use of a point of care antibody test in a physician’s office to determine which patients have developed antibodies, indicating an immune response to SARS-CoV-2, and to assist with decisions on whether patients should pursue normal social and workplace activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".