Can spiral analysis predict the FP‐CIT SPECT scan result in tremulous patients?
Bibliographic record
Abstract
BACKGROUND: Previous studies have compared the accuracy of spiral analysis in distinguishing essential tremor (ET) from PD. In this study, we have used this technique to distinguish cases of tremulous PD (TDPD) (N = 24) from tremulous parkinsonian subjects without evidence of dopaminergic deficit (N = 41). METHODS: All patients were characterized on clinical and (123)I-N-ω-fluoro-propyl-2ß-carbomethoxy-3ß-(4-iodophenyl) nortropane ([(123)I] FP-CIT) SPECT scan data, which were concordant in every case. All analyses were carried out by observers blinded to the clinical details and supplied with just the spiral drawings, from which tremor severity (TS), 3-turn spiral diameter (3TD), and spiral density (SD) were measured. RESULTS: The spirals drawn by TDPD cases had significantly smaller 3TD (P = 0.029) and greater SD (P = 0.0082) than those with normal FP-CIT scans. There was no significant difference in the TS between the two groups (P = 0.11). The sensitivity and specificity of TS were 62.5% and 65.0%, 3TD were 75% and 56.7%, and SD were 30.4% and 82.5%, respectively, in predicting the correct classification. Further analyses combining these factors into pairs, showed that the respective sensitivities and specificities of (1) TS × 3TD were 75.0% and 40.0%, (2) TS/SD were 56% and 70.0%, and (3) 3TD/SD were 87.0% and 40.0%. DISCUSSION: There are significant differences in the 3TD and SD of spirals drawn by tremulous patients with normal versus abnormal FP-CIT scans. Spiral analysis may have some clinical value in helping to distinguish tremulous parkinsonian patients with normal presynaptic dopaminergic imaging from tremulous PD patients, providing results similar to those reported for expert movement disorder neurologists using standardized videotaped examinations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 teacher head, 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".