Central Post Stroke Pain: Clinical, MRI, and SPECT Correlation
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to report clinical spectrum of central post stroke pain (CPSP) and correlate these with magnetic resonance imaging (MRI) and single photon emission computed tomography (SPECT) findings. DESIGN: The study was designed as a prospective study. SETTING: The study was set in a tertiary care teaching hospital. SUBJECT AND METHOD: Twenty-three consecutive CPSP patients were included and their severity of pain, sensory threshold, allodynia, hyperalgesia, and temporal summation were assessed by quantitative sensory testing (QST). Cranial MRI and (99)Tc ethylene cystine dimmer SPECT findings correlated with QST. RESULTS: The duration of CPSP was 5 months (0.25-108). Allodynia was present in 12 patients, punctuate hyperalgesia in 11, and temporal summation in 12. SPECT was abnormal on visual analysis in 17 patients; hypoperfusion in corresponding thalamus in nine, and parietal cortex in 11 patients. Semiquantitative analysis revealed hyperperfusion of thalamus in four and parietal cortex in five patients. MRI revealed infarction in 14 and hematoma in nine patients. The QST findings were similar in thalamic and extrathalamic CPSP. The MRI and SPECT findings were also not different in CPSP patients with and without allodynia. CONCLUSION: The QST findings in patients with CPSP were similar in patients with thalami and extrathalamic lesions. SPECT and MRI findings were also not different in CPSP patients with and without allodynia.
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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 | 0.001 | 0.000 |
| 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) | 0.004 | 0.001 |
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".