Impact of COVID-19 on hospitalization, death rate, and other inpatient measures among Asian patients in hospitals in California
Bibliographic record
Abstract
Objective: This study aims to analyze COVID-19 hospitalization and death rate in the Asian population of a predominantly Asian-serving multi-hospital system (ASMHS).Methods: The COVID-19 patient information was collected electronically from March 1 to November 12, 2020, including demographics, insurance, mortality, ICU admissions, and length of stay (LOS). Demographic characteristics were compared with the county-level and national data. A comparison of hospital LOS between Asians and non-Asians was conducted.Results: The prevalence ratio of deaths in Asians at ASMHS was 1.29, which was 53% higher than the county and 77% higher than the nation. The ICU admission for ASMHS Asian patients was 11.8% compared to 5.6% for non-Asian. Overall Asians and Asians aged > 65 had significantly longer LOS than non-Asians (p < .001).Conclusions: High prevalence ratio of deaths was noted in ASMHS’s Asian patients which may be related to older age, higher ICU rate, and longer LOS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".