Obesity and Higher Risk for Severe Complications of Covid-19: What to do when the two pandemics meet
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has spread around the globe, infecting more than ten million individuals, with more than 500,000 dead; about one half of the infected people have recovered. Despite this fact, a subgroup of individuals affected by COVID-19 is at greater risk of developing worse outcomes and experience a high rate of mortality. Data on the association between obesity and COVID-19 are growing; the available studies, have reported a high prevalence of overweight and obesity in patients experiencing a severe COVID-19 course, with serious complications requiring hospitalization and admission to intensive care units. This paper attempts to highlight potential mechanisms behind the greater vulnerability to COVID-19 of individuals with obesity. The presence of uncontrolled chronic obesity-related comorbidities, particularly pulmonary diseases, can present a primary fertile soil for respiratory tract infection. Combined with immune system impairments, such as alteration in the T-cell proliferation and macrophage differentiation, and the high pro-inflammatory cytokine production by the adipose organ, this may worsen the general condition toward a systemic diffusion of infection. Prevention remains the first line of intervention in these patients that can be achieved by adhering to social distancing and adopting hygiene precautions, combined with a healthy lifestyle. Patients with obesity require preferential access dedicated to primary care services to ensure they are regularly taking their medications for the treatment of any concurrent chronic diseases. Finally, their physicians must promptly manage any medical signs or symptoms in the case of suspected severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) infection to prevent the risk of severe outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".