The evaluation of distal symmetric polyneuropathy: utilisation and expenditures by community neurologists
Bibliographic record
Abstract
Previous studies show that electrodiagnostic tests and MRIs are frequently ordered in the initial evaluation of neuropathy.1 ,2 However, American Academy of Neurology (AAN) guideline-supported tests, particularly the glucose tolerant test (GTT), are often omitted.1 Recent evidence suggests that electrodiagnostic studies and MRIs are the primary drivers of expenditures associated with neuropathy testing despite limited data to support their use.3 However, these results are based on Medicare claims; therefore, it remains unclear if this observation applies to other populations and when using a more rigorous case definition of neuropathy. Furthermore, Medicare claims do not provide detailed clinical information that would allow for investigation of patient-level factors associated with utilisation and expenditures. Our aim was to determine utilisation and expenditures in the evaluation of a new diagnosis of distal symmetric polyneuropathy (DSP) by community neurologists using a population-based design and a strict case definition. We also sought to determine which patient and physician factors were associated with testing expenditures, electrodiagnostic and MRI utilisation. We attempted to capture all new patients with DSP seen by community neurologists in Nueces County, Texas as previously described.4 Patients were required to meet the Toronto consensus panel definition of probable neuropathy and have a documented neuropathy diagnosis. From 1 April 2010 to 31 March 2011, we used a validated International Classification of Diseases 9 case capture technique to screen all new patient visits for cases followed by medical record abstraction to confirm that they met our DSP definition.5 The aetiology at the time of the initial visit to the neurologist was determined by the neurologist's documented …
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.010 |
| 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; both teacher heads agree on what is shown here.
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".