COVID-19: Vitamin A deficiency and rhino-orbital mucormycosis (Black Fungus)
Bibliographic record
Abstract
Mucormycosis is a serious and fatal disease characterized by rhino-orbital and cerebral involvement caused by a rare but opportunistic fungal pathogen. Mucormycosis, also known as black fungus, caused fear and panic with a sudden and devastating rise in India during the second wave of the COVID-19 epidemic (April to June 2021). Although the reason for the sharp rise of mucormycosis in the COVID-19 epidemic is still controversial, its frequent occurrence in diabetic COVID-19 patients has associated mucormycosis with diabetes. However, the fact that mucormycosis is also seen in isolated vitamin A deficiency, non-diabetic COVID-19 patients, measles, and AIDS patients suggests that vitamin A deficiency may be under the pathogenetic mechanism. Vitamin A deficiency has previously been shown to develop in measles, AIDS, and COVID-19. Mucormycosis is an opportunistic infection mainly seen in people whose immune system is suppressed due to malignancy, chemotherapy, and AIDS. It is known that vitamin A deficiency also causes a kind of nutritional immunodeficiency picture. Therefore, the tendency to fungal, viral, and bacterial infections increases in vitamin A deficiency, and eye involvement is also common. Vitamin A deficiency also causes decreased tear secretion and deterioration of the anatomical/physiological defense barrier of the eye. In vitamin, A deficiency, besides microbial keratitis in the eye, night blindness, xerophthalmia, conjunctivitis (pink eye), Bitot spots, keratomalacia, and retinopathy also develop. Night blindness is considered the first sign of vitamin A deficiency, while Xerophthalmia is pathognomonic for vitamin A deficiency. We think that vitamin A deficiency is responsible for mucormycosis seen in COVID-19 patients and that vitamin A replacement with antifungals may have preventive and therapeutic value against COVID-19-related mucormycosis and other ocular symptoms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".