Analysis of Risk Factors of Soft Tissue Bleeding in COVID-19 Patients: A Point of View After Two Years of Pandemic
Bibliographic record
Abstract
Background: The aim of the study was to analyze the relationship between patient characteristics, including anagraphic and laboratoristic data and amount of adipose tissue measured in computed tomography (CT) scans in coronavirus disease 2019 (COVID-19) patients, and incidence of soft tissue bleeding requiring medical and/or interventional radiology management. Methods: A total of 132 patients hospitalized for COVID-19 pathology from October 2020 to May 2021 were included in the study and divided into two groups: a bleeding group of 70 cases with soft tissue bleeding occurring during hospitalization, and a control group of 62 hospitalized COVID-19 patients without bleeding events. In the bleeding group, two subgroups were considered: an embolization group including soft tissue bleeding cases requiring interventional radiology with transarterial embolization (TAE) (16/70; 22.9%) and a non-embolization group, clinically managed without TAE (54/70; 77.1%). Demographics and clinical data, visceral adipose tissue (VAT) area and subcutaneous adipose tissue (SAT) area measured on CT images and VAT/SAT ratio were compared between bleeding and control groups and between embolization and non-embolization subgroups. Results: Bleeding and control groups did not significantly differ for sex distribution, COVID-19, platelet (PLT) count, international normalized ratio (INR), SAT area, VAT area, and VAT/SAT ratio. Embolization and non-embolization groups did not significantly differ for age, COVID-19, PLT count, INR, SAT area, and VAT/SAT ratio. Bleeding group had lower body mass index (BMI) than control group as well as embolization group compared to non-embolization group. A statistically significant difference was observed between embolization and non-embolization groups for VAT area, with smaller values in embolization group (mean difference: 64.2 cm 2 , 95% confidence interval: 8.3 - 120.1; P < 0.05). Conclusion: Soft tissue bleeding in COVID-19 is more frequent and severe in patients with low amount of VAT, demonstrating that fat mass may have a containing function on bleeding, limiting its progression in surrounding structures. There are some other factors that influence the risk of bleeding, such as age, thromboprophylaxis therapy and BMI. J Clin Med Res. 2022;14(5):188-195 doi: https://doi.org/10.14740/jocmr4708
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".