Spectrum of neurological involvement in mucormycosis following COVID 19: A single tertiary centre study
Bibliographic record
Abstract
Background: This study aims to describe the clinical and imaging spectrum of neurological involvement in rhino-orbital cerebral mucormycosis (ROCM) following COVID. In this observational study, all patients with confirmed COVID associated mucormycosis were recruited. Consecutive patients with neurological signs and symptoms or patients with evidence of neurological involvement based on imaging were evaluated. MRI of brain and paranasal sinuses were done in 3T MRI scanner and evaluated by a radiologist. Results: A total of 182 patients were recruited into the study out of which 72 (39.56%) patients had neurological involvement. The mean age of the patients was 50.31±11.06 (Range: 33-83) years. A male preponderance was noted with 56 (74.67%) patients being male. The commonest symptom reported was unilateral vision impairment and periorbital swelling. Patients were noted to have both fulminant and indolent course of illness. Clinical evidence of neurological and orbital involvement was observed in 33 and 55 patients, respectively. Meningeal involvement (50%) was the commonest imaging finding noted in our study. Other common findings noted were skull- based osteomyelitis (44.44%), cavernous sinus thrombosis (29.17%), intracranial abscess (27.78%), cerebritis (22.22%), infarcts (33.33%), neuritis and intracranial haemorrhage (2.78%). Conclusion: This study reports one of the largest single centre cohorts with neurological findings in COVID associated mucormycosis. COVID associated mucormycosis can present with plethora of neurological manifestations in imaging, such as infarct, intracranial and extracranial abscess, neuritis and nerve abscess, sinus thrombosis that may or may not be accompanied by focal neurological deficit corresponding to the anatomical involvement.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".