Hydroxychloroquine pre-exposure prophylaxis to prevent SARS-CoV-2 among health care workers at risk for SARS-CoV-2 exposure: A nonrandomized controlled trial
Bibliographic record
Abstract
Abstract Background Aerosol-generating procedures increase the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care workers (HCWs). An effective pre-exposure prophylaxis would mitigate this risk. Objective To determine the efficacy of pre-exposure prophylactic hydroxychloroquine for the prevention of SARS-CoV-2 infection and symptomatic coronavirus 19 disease (COVID-19) among HCWs at high occupational risk of SARS-CoV-2 exposure. Methods 130 HCWs in the New York University Langone Health System (NYULHS) who performed aerosol-generating procedures on patients with COVID-19 or provided bedside care for inpatients with COVID-19 or persons with suspected COVID-19 in an emergency department, for at least three shifts in a 7-day period, during the first 2020 COVID-19 wave in New York City were enrolled. Participants elected to take oral hydroxychloroquine, 600 mg on day 1 followed by 200 mg daily, or not take hydroxychloroquine for up to 90 days. Participants self-collected dried blood spots and completed digital questionnaires regarding COVID-19 symptoms, adverse events, and other COVID-19 medication use. Results Six participants (7.5%) seroconverted during the trial: four who took hydroxychloroquine (6.8%) and two who declined hydroxychloroquine (9.5%). All participants not taking hydroxychloroquine reported COVID-19 symptoms at seroconversion compared to one of four participants (25%) who took hydroxychloroquine. Adverse events occurred in eight participants (9.6%) on hydroxychloroquine and were mostly mild. Conclusions This study ( ClinicalTrials.gov NCT04354870 ) did not demonstrate a statistically significant difference in SARS-CoV-2 seroconversion associated with hydroxychloroquine pre-exposure prophylaxis among HCWs at high risk of occupational SARS-CoV-2 exposure, although was underpowered and a high rate of hydroxychloroquine discontinuation was observed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".