Survival, mortality, and related comorbidities among COVID-19 patients in Saudi Arabia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To assess the survival of COVID-19 patients in Saudi Arabia and to investigate possible mortality predictors. METHODS: This is a retrospective cohort study involving 248 patients with severe acute respiratory syndrome coronavirus-2 who were admitted to the primary COVID-19 referral hospital in Jeddah between March and June of 2020. Socio-demographic characteristics, comorbidities, laboratory investigations, management protocols, complications, treatment options, and mortality data were extracted from electronic medical records. The time analysis began at the first signs of illness thorough discharge or death. RESULTS: =0.05). We did not find a significant benefit in relation to any treatment option. CONCLUSION: Age, asthma, some in-hospital complications are important survival indicators in hospitalized COVID-19 patients. The controllable co-factors should be monitored and managed by healthcare workers to reduce mortality rates in those hospitalized with COVID-19.
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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 | 0.006 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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