Clinical Features of Fatalities in Patients With COVID-19
Bibliographic record
Abstract
OBJECTIVES: The novel coronavirus disease 2019 (COVID-19) pandemic has spread to over 213 countries and territories. We sought to describe the clinical features of fatalities in patients with severe COVID-19. METHODS: We conducted an Internet-based retrospective cohort study through retrieving the clinical information of 100 COVID-19 deaths from nonduplicating incidental reports in Chinese provincial and other governmental websites between January 23 and March 10, 2020. RESULTS: Approximately 6 of 10 COVID-19 deaths were males (64.0%). The average age was 70.7 ± 13.5 y, and 84% of patients were elderly (over age 60 y). The mean duration from admission to diagnosis was 2.2 ± 3.8 d (median: 1 d). The mean duration from diagnosis to death was 9.9 ± 7.0 d (median: 9 d). Approximately 3 of 4 cases (76.0%) were complicated by 1 or more chronic diseases, including hypertension (41.0%), diabetes (29.0%) and coronary heart disease (27.0%), respiratory disorders (23.0%), and cerebrovascular disease (12.0%). Fever (46.0%), cough (33.0%), and shortness of breath (9.0%) were the most common first symptoms. Multiple organ failure (67.9%), circulatory failure (20.2%), and respiratory failure (11.9%) are the top 3 direct causes of death. CONCLUSIONS: COVID-19 deaths are mainly elderly and patients with chronic diseases especially cardiovascular disorders and diabetes. Multiple organ failure is the most common direct cause of death.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".