Prior antibiotic exposure is associated with worse outcomes in adults with COVID-19
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Antibiotic-induced perturbations of the gut microbiome impair immunologic responses but whether they influence disease severity is unknown. The COVID-19 pandemic provided a unique opportunity to explore this question given widespread testing for SARS-CoV-2 infections. OBJECTIVE: To determine whether prior antibiotic exposure was associated with outcomes in patients with COVID-19. METHODS: Retrospective cohort study of all community-dwelling adults in Alberta, Canada with COVID-19 between March 2020 and June 2023. Subjects with antibiotic dispensations in the prior 3 months were compared (using multivariable logistic regression and propensity score (PS)-matching) to those without antibiotic exposure for differences in 30-day outcomes. RESULTS: Of 445,646 adults with COVID-19, 49,581 (11.1%) were exposed to at least one antibiotic course in the prior 3 months. Those exposed to antibiotics were more likely to present to an emergency department (13.4% vs. 7.4%, aOR 1.52, 95%CI 1.48-1.57, PS-matched OR 1.48, 1.42-1.54), be hospitalised (5.8% vs. 2.8%, aOR 1.40,1.33-1.46, PS-matched OR 1.37, 1.29-1.45), or die (1.7% vs. 0.6%, aOR 1.28, 1.18-1.40, PS-matched OR 1.27, 1.14-1.42) than patients without prior antibiotic exposure. The associations were similar whether the antibiotic prescriptions were appropriate or not or whether antibiotic exposure periods were 6 weeks, 6 months, or 12 months prior to the positive RT-PCR test. The associations were stronger in those individuals with the highest tertile of antibiotic exposure, or those exposed to broad-spectrum antibiotics, or younger patients. CONCLUSION: Prior antibiotic exposure is associated with worsened disease severity in patients infected with SARS-CoV-2. These findings support efforts to reduce antibiotic use.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it