SARS-CoV-2 Clinical Characteristics and Viral Shedding in Kuwait
Bibliographic record
Abstract
OBJECTIVES: We aimed to describe the clinical characteristics of SARS-CoV-2 infection and estimate viral shedding duration in respiratory specimens. METHODS: A retrospective cohort study was performed from February 25 to March 25, 2020. In Kuwait, all suspected coronavirus disease 2019 (COVID-19) cases, contacts of cases, and returning travelers were systematically tested for SARS-CoV-2 by RT-PCR. All infected persons, regardless of symptoms, were hospitalized and serially tested until they had two negative results. Descriptive statistics and regression analyses were performed. RESULTS: Two hundred seven cases of SARS-CoV-2 infection were included in this study. About half of the cases were asymptomatic and 1.9% died. The median time to negative RT-PCR was 22 days. Increasing age, ARDS, and low peripheral white blood cell count were associated with prolonged PCR positivity. CONCLUSION: Predictors for prolonged RT-PCR positivity included increasing age, ARDS, and low white blood cell count. The findings of this study may aid in better understanding of the epidemiology of SARS-CoV-2 infection and molecular testing dynamics.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".