Clinical characteristics and in-hospital mortality of COVID-19 adult patients in Saudi Arabia
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Bibliographic record
Abstract
OBJECTIVES: To provide a detailed study of demographic, baseline comorbidities, clinical features, and outcome for Coronavirus disease 2019 (COVID-19) patients. METHODS: A record-based case-series study conducted from March 23 to June 15, 2020 in King Saud Medical City, Riyadh, Saudi Arabia. Demographic data, clinical presentation, laboratory investigations, complications, and in-hospital outcome of COVID-19 patients collected with analysis of the clinical characteristics for survivors and deceased. RESULTS: A total of 768 patients were included. The mean age was 46.36±13.7 years and 76.7% were men. Approximately 96.3% reported more than one comorbidity; diabetes mellitus was the most frequent (46.4%). Fever (84.5%), cough (82.3%), and shortness of breath (79.8%) were the main presenting symptoms. During the follow-up, pneumonia reported in 68.6%, acute respiratory distress syndrome in 32.7%, septic shock in 20.7%, respiratory failure in 20.3%, and acute kidney injury in 19.3%. Approximately 45.8% of enrolled patients required intensive care unit admission. Lung disease (odd ratio [OR]=3.862 with 95% confident interval [CI] (2.455-6.074), obesity (OR=3.732, CI=2.511-5.546), smoking (OR=2.991, CI=2.072-4.317), chronic kidney disease (OR=2.296. CI=1.497-3.521), and diabetes mellitus (OR=2.291, CI=1.714-3.063) are predictors of ICU admission. Fatality ratio was 4.27%; therefore, men were more prevalent in dead group. CONCLUSION: Coronavirus disease 2019 places a huge burden on healthcare facilities, particularly in patients with comorbidity. Coronavirus disease 2019 patients who are obese and smokers with history of diabetes mellitus have a high risk of death.
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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 | 0.003 | 0.351 |
| 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 | 0.002 |
| 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 it