Outcomes in Patients With COVID-19 Disease and High Oxygen Requirements
Bibliographic record
Abstract
BACKGROUND: Approximately 19% of people infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) progress to severe or critical stages of the coronavirus disease 2019 (COVID-19) with a mortality rate exceeding 50%. We aimed to examine the characteristics, mortality rates, intubation rate, and length of stay (LOS) of patients hospitalized with COVID-19 disease with high oxygen requirements (critically ill). METHODS: We conducted a retrospective analysis in a single center in Brooklyn, New York. Adult hospitalized patients with confirmed COVID-19 disease and high oxygen requirements were included. We performed multivariate logistic regression analyses for statistically significant variables to reduce any confounding. RESULTS: A total of 398 patients were identified between March 19th and April 25th, 2020 who met the inclusion criteria, of which 247 (62.1%) required intubation. The overall mortality rate in our study was 57.3% (n = 228). The mean hospital LOS was 19.1 ± 17.4 days. Patients who survived to hospital discharge had a longer mean LOS compared to those who died during hospitalization (25.4 ± 22.03 days versus10.7 ± 1.74 days). In the multivariate analysis, increased age, intubation and increased lactate dehydrogenase (LDH) were each independently associated with increased odds of mortality. Diarrhea was associated with decreased mortality (OR 0.4; CI 0.16, 0.99). Obesity and use of vasopressors were each independently associated with increased intubation. CONCLUSIONS: In patients with COVID-19 disease and high oxygen requirements, advanced age, intubation, and higher LDH levels were associated with increased mortality, while diarrhea was associated with decreased mortality. Gender, diabetes, and hypertension did not have any association with mortality or length of hospital stay.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".