Endotoxemia in Critically Ill Patients with COVID-19
Bibliographic record
Abstract
INTRODUCTION: Mechanism(s) mediating critical illness in coronavirus disease 2019 (COVID-19) remain unclear. Previous reports demonstrate the existence of endotoxemia in viral infections without superimposed gram-negative bacteremia, but the rate and severity of endotoxemia in critically ill patients with COVID-19 requires further exploration. MATERIALS AND METHODS: This is a single-center cross-sectional study of 92 intensive care unit patients diagnosed with COVID-19 pneumonia. Endotoxin activity (EA) was measured in patients that met the following criteria: (1) age ≥18 years and (2) multi-organ dysfunction score >9 from March 24, 2020, to June 20, 2020. RESULTS: A total of 32 patients met the inclusion/exclusion criteria for measurement of EA. The median age of the study cohort was 60 years with a majority male (21/32, 65%) with hypertension (50%). A significant proportion of the patients exhibited either elevated EA in the intermediate range (0.40-0.59 EA units) (10/32, 31%) or high range (≥0.60 EA units) (14/32, 44%) or were nonresponders (NRs, low neutrophil response) to EA (6/32, 19%), with the presence of gram-negative bacteremia only in 2/32 (6%) patients. Low EA was reported in 2/32 patients. NRs (5/6, 83%) and patients with high EA (7/14, 50%) exhibited higher acute kidney injury (AKI) as compared to patients with low/intermediate EA level (1/12, 8.3%). DISCUSSION/CONCLUSION: Elevated EA was observed in a large majority of critically ill patients with COVID-19 and multi-organ dysfunction despite a low incidence of concurrent gram-negative bacteremia. While we observed that elevated EA and nonresponsiveness to EA were associated with AKI in critically ill patients with COVID-19, these findings require further validation in larger longitudinal cohorts.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".