Epidemiology and Disease Burden of Mucormycosis in Canada: Canmus Registry
Bibliographic record
Abstract
Background The burden of mucormycosis has increased with the expansion of risk groups and improved diagnosis. Although diabetes mellitus has been the leading risk factor for mucormycosis globally, the emergence of risk groups such as hemato-oncology patients, allogeneic bone marrow transplantation and solid organ transplantation have shifted the epidemiology of mucormycosis. There is a paucity of literature describing the burden, clinical presentation, treatment and outcomes of mucormycosis in Canada. CANMUS (Canadian Mucormycosis Study)is a national registry with broad geographical representation ,that will assess the epidemiology and clinical outcomes of Canadian patients affected by mucormycosis. Here we assess the outcomes at 6 and 12 weeks of therapy and last clinical assessment. Methods This retrospective registry involving 15 centers across Canada, from 1/1/2009 to 1/31/2020 using pathology/microbiology records to identify proven cases of mucormycosis in patients ≥18 years of age. Patient medical record data were collected and reported in a web-based data management program (REDCap). Descriptive statistics analyzed both categorical and continuous data. Cox proportional hazards models were used to explore risk factors for 6 and 12-week survival. Logistical regression was employed to investigate factors associated with positive clinical outcomes (defined as partial or complete response versus stable disease or progression). Results Interim data was available on 108 patients. The mean age was 53 (range 20-91) and 55.6% were male patients. The leading diagnostic risk factor for mucormycosis was hematological malignancy (50.9%, of which AML comprised 54.5%) followed by diabetes mellitus (25%). The most common sites of infection were: pulmonary (42.6%) rhino-sinus and/or orbital and/or cerebral (22.2%) and cutaneous (18%). The distribution of pathogens was: Mucor spp. (45.2%), Rhizopus spp. (34.5%) and Lichtheimia spp. (10.7%). Clinical response (composite of complete and partial responses) at 6 and 12 weeks was 31% and 29%, respectively. Survival analyses will be presented using hazard ratios and confidence intervals (CI). Logistic regression of factors associated with a positive clinical response will also be presented. Conclusions The epidemiology of mucormycosis in Canada is evolving. Hematological malignancies rather than diabetes are the major predisposing risk factor for mucormycosis with Mucor spp. being the predominant pathogen. Despite modest advances in therapies, outcomes remain poor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".