<sup>123</sup>I-MIBG myocardial scintigraphy for the diagnosis of DLB: a multicentre 3-year follow-up study
Bibliographic record
Abstract
Background and purpose We previously reported the usefulness of iodine-123 metaiodobenzylguanidine (123I-MIBG) myocardial scintigraphy for differentiation of dementia with Lewy bodies (DLB) from Alzheimer’s disease (AD) in a cross-sectional multicentre study. The aim of this study was, by using reassessed diagnosis after 3-year follow-up, to evaluate the diagnostic accuracy of 123I-MIBG scintigraphy in differentiation of probable DLB from probable AD. Methods We undertook 3-year follow-up of 133 patients with probable or possible DLB or probable AD who had undergone 123I-MIBG myocardial scintigraphy at baseline. An independent consensus panel made final diagnosis at 3-year follow-up. Based on the final diagnosis, we re-evaluated the diagnostic accuracy of 123I-MIBG scintigraphy performed at baseline. Results Sixty-five patients completed 3-year follow-up assessment. The final diagnoses were probable DLB (n=30), possible DLB (n=3) and probably AD (n=31), and depression (n=1). With a receiver operating characteristic curve analysis of heart-to-mediastinum (H/M) ratios for differentiating probable DLB from probable AD, the sensitivity/specificity were 0.77/0.94 for early images using 2.51 as the threshold of early H/M ratio, and 0.77/0.97 for delayed images using 2.20 as the threshold of delayed H/M ratio. Five of six patients who were diagnosed with possible DLB at baseline and with probable DLB at follow-up had low H/M ratio at baseline. Conclusions Our follow-up study confirmed high correlation between abnormal cardiac sympathetic activity evaluated with 123I-MIBG myocardial scintigraphy at baseline and the clinical diagnosis of probable DLB at 3-year follow-up. Its diagnostic usefulness in early stage of DLB was suggested. Trial registration number UMIN00003419.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".