COVID-19 Outcome Relates With Circulating BDNF, According to Patient Adiposity and Age
Bibliographic record
Abstract
Background and Aims: We evaluated adipose tissue-derived hormones, body composition, serum metabolic profile, levels of brain-derived neurotrophic factor (BDNF), and the association of these parameters with the clinical outcome in patients with COVID-19. We sought to examine whether obesity, sex, and age influence the adipose tissue endocrine response to the disease. Methods: This prospective study investigated 145 hospitalized patients with COVID-19. Patients were categorized based on their body mass index (BMI), sex and age, and were also classified regarding their outcome after hospitalization as: (a) Non-ICU: patients hospitalized who did not receive intensive care; (b) ICU-survivor: patients admitted to the intensive care unit and discharged; (c) ICU-death: patients who died. Blood samples were collected by the hospital staff between the first and third day of hospitalization. Serum leptin, adiponectin and BDNF concentrations, triglycerides, total cholesterol and cholesterol fractions were performed following the manufacturer's guidelines. Results: We demonstrate that BDNF levels predict intensive care (IC) need ( p < 0.01). This association was found to be stronger in patients >60y ( p = 0.026). Neither leptin nor adiponectin concentration was associated with IC requirement or with patient's outcome, while the BDNF/adiponectin ratio was closely associated with worsened outcomes ( p < 0.01). BDNF concentration was similar between sexes, however tended to be lower in male patients ( p = 0.023). In older patients, BDNF concentration was lower than that of younger patients ( p = 0.020). These age and sex-specific differences should be considered when employing these potential markers for prognosis assessment. While appetite and body composition regulating hormones secreted by the white adipose tissue are not reliable predictors of disease severity, the ratio BDNF/adiponectin was indicative of patient status. Conclusion: Thus, we propose that serum BDNF content and BDNF/adiponectin ratio may serve as tools predicting worsened prognosis in COVID-19, especially for male patients.
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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 | 0.000 | 0.002 |
| 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".