Hemisensory syndrome is associated with a low diagnostic yield and a nearly uniform benign prognosis
Bibliographic record
Abstract
OBJECTIVE: To describe the diagnostic yield and prognosis for patients with hemisensory syndrome. BACKGROUND: The aetiology, utility of diagnostic procedures, and outcome of hemisensory syndrome in patients with exclusive hemibody complaints having only subjective sensory abnormalities on examination is unknown. METHODS: Patients were prospectively identified with hemisensory syndrome in a tertiary care institution from 1998-2002. Diagnostic procedures were analysed for sensitivity and clinical follow up was performed. RESULTS: Thirty four patients, 25 (74%) women, of age 35 (SD 11) years were identified. The hemisensory syndrome occurred on the left side in 23 (68%) cases. Neuroimaging of the brain demonstrated diagnostic abnormalities representing ischaemic aetiology in one case. Other diagnostic testing including cerebrospinal fluid examination, electrophysiological testing, carotid ultrasonography, echocardiography, and blood testing revealed no diagnostic abnormalities. Sixteen patients (47%) continued to complain of hemisensory difficulties after all investigations were completed at 9.6 (5.8) days. One patient with a history of systemic lupus erythematosus and positive antiphospholipid antibodies had a second event diagnosed as stroke seven months after presentation. Clinical follow up at 16 (7) months revealed persisting symptoms in 6 (20%) of 30 patients. Six (50%) of 12 patients agreeing to psychiatric assessment received diagnoses of personality or mood disorders. CONCLUSIONS: Diagnostic yield in hemisensory syndrome is low, and prognosis is almost always uniformly benign. The author advocates careful assessment of medical history and consideration for neuroimaging in this group of patients.
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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 | 0.001 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".