Clinical Course, Radiologic Features and Treatment Response in Patients with Tumefactive Demyelinating Lesions in Toronto (P4.018)
Bibliographic record
Abstract
OBJECTIVE: To describe demographic and clinical features of individuals with tumefactive demyelinating lesions (TDLs) to determine the disease course, treatment response and proportion with prior diagnosis or subsequent development of multiple sclerosis (MS). BACKGROUND: TDLs differ from typical demyelinating lesions, as they are greater than 2 cm, may display edema and mass effect, and often mimic tumors or abscesses. Clinical and radiologic features differ from typical MS, leading to difficulty in diagnosis and management. DESIGN/METHODS: A retrospective observational multi-center study of 30 individuals [70[percnt] female] with TDLs in Toronto between 1999-2014. Data included demographic features, clinical course, disability (Expanded Disability Status Scale (EDSS)), radiologic features and treatment response. RESULTS: Mean age at TDL onset was 41 years and 82[percnt] had polysymptomatic onset with a median EDSS of 4. The TDL was the first demyelinating event in 25 (83[percnt]), of which 4 met McDonald criteria for MS while 21 were Clinically Isolated Syndrome (CIS). Six of the CIS (29[percnt]) converted to MS at follow up (mean 2.7 years). Six (20[percnt]) had recurrent TDL episodes. Most lesions (98[percnt]) enhanced and the mean size of well-defined lesions was 2.7 by 2.4 cm. Eighty-seven percent were treated with high-dose steroids and 75[percnt] improved. Seven received plasmapheresis and four cyclophosphamide due to poor steroid response. Twenty-seven (73[percnt]) had partial and 10 (27[percnt]) complete recovery. Median EDSS at follow up was 1 in those with a single TDL, but 6 in those with recurrent TDLs. Radiologically, 89[percnt] of lesions decreased in size and 82[percnt] had resolution of enhancement. Disease modifying therapy was used in 43[percnt], typically in those diagnosed with MS. CONCLUSIONS: Individuals with TDLs remain a diagnostic and management challenge given atypical clinical and radiologic features, but not all require biopsy. Many remain CIS or develop typical relapsing-remitting MS, but a subset has recurrent TDLs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".