Epidemiological Characteristics and Clinical Features of Patients Infected With the COVID-19 Virus in Nanchang, Jiangxi, China
Bibliographic record
Abstract
Objectives: The 2019 novel coronavirus disease (COVID-19) pandemic is the biggest public health crises in the 21st century. While most patients infected with the COVID-19 virus have no to moderate symptoms, there is currently limited clinical information about these patients. Methods: In this study, we retrospectively investigated 41 patients infected with the COVID-19 virus in Nanchang, Jiangxi province, China, from February 4 to March 2, 2020. Nanchang is about 260km southeast of Wuhan, the initial epicenter of the COVID-19 pandemic. We retrieved information on patient demographics, physical examination results, epidemiology, clinical manifestations, underlying conditions, laboratory analyses, radiological images, and treatment outcomes. Results: Most patients (70.7%) had a history of close contact with patients with confirmed COVID-19, and 16 patients (39.0%) showed a high degree of family clustering. All 41 patients had no to moderate symptoms. The median age was 39.9 years and common symptoms of illness were fever (69.2%), cough (65.4%), and fatigue (19.2%). The dominant patient group was middle-aged women, with hypertension (14.6%) and chronic liver disease (12.2%) as the most frequent underlying conditions. All patients recovered, with the mean time of viral nucleic acid clearance at 10.6 days. Chest CT scans presented ground-glass opacities in 53.7% of patients while 26.8% had normal CT images. Laboratory results showed that lymphocyte counts, lymphocyte percentages, ESR, CRP, IgG, Fib, and cytokines were correlated to patients' conditions. Approximately 60% to 90% of patients had abnormally high levels of cytokines IL-4, IL-6, IL-10, and/or TNF-α. Conclusions: Our results showed variable clinical and laboratory presentations among this group of patients infected with the COVID-19 virus. Though all 41 patients recovered, our results suggest that cytokine levels and other biochemical indicators should be monitored for patients infected with the COVID-19 virus showing no to moderate symptoms to ensure quick access for critical medical attention, if needed.
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How this classification was reachedexpand
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 | 0.002 | 0.167 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".