Clinical Characteristics of 2019 Novel Infected Coronavirus Pneumonia: A Systemic Review and Meta-analysis
Bibliographic record
Abstract
ABSTRACT Background A novel pneumonia associated with the 2019 coronavirus infected pneumonia (NCIP) suddenly broke out in Wuhan, China in December 2019. 37287 confirmed cases and 813 death case in China (Until 8th/Feb/2019) have been reported in just fortnight. Although this risky pneumonia with high infection rates and high mortality rates need to be resolved immediately, major gaps in our knowledge of clinical characters of it were still not be established. The aim of this study is to summaries and analysis the clinical characteristics of 2019-nCoV pneumonia. Methods Literatures have been systematically performed a search on PubMed, Embase, Web of Science, GreyNet International, and The Cochrane Library from inception up to February 8, 2020. The Newcastle-Ottawa Scale was used to assess quality, and publication bias was analyzed by Egger’s test. In the single-arm meta-analysis, A fix-effects model was used to obtain a pooled incidence rate. We conducted subgroup analysis according to geographic region and research scale. Results A total of nine studies including 356 patients were included in this study, the mean age was 52.4 years and 221 (62.1%) were male. The pooled incidences rate of symptoms as follows: pharyngalgia (12.2%, 95% CI: 0.087-0.167), diarrhea (9.2%, 95% CI: 0.062-0.133) and headache (8.9%, 95% CI: 0.063-0.125). Meanwhile, 5.7% (95% CI: 0.027-0.114) of patients were found without any symptoms although they were diagnosed by RT-PCR. In the terms of CT imaging examination, the most of patients showed bilateral mottling or ground-glass opacity, 8.6% (95% CI: 0.048-0.148) of patients with crazy-paving pattern, and 11.5% (95% CI: 0.064-0.197) of patients without obvious CT imaging presentations. The pooled incidence of mortality was 8.9% (95% CI: 0.062-0.126). Conclusions To our knowledge, this is the first evidence-based medicine research to further elaborate the clinical characteristics of NCIP, which is beneficial to the next step of prevention and treatment.
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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 | 0.004 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.024 | 0.007 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".