Defining the Clinical Syndrome of Lumbar Spinal Stenosis: A Recursive Specialist Survey Process
Bibliographic record
Abstract
BACKGROUND: Lumbar spinal stenosis has evolved from an anatomic concept to a poorly defined clinical syndrome. Rules for such a syndrome need to be informed by the experience and beliefs of expert clinicians. The level of certainty is seldom considered in defining criteria for a syndrome. OBJECTIVE: To design an innovative online recursive survey technique to seek out information that is valued by specialists and to measure the impact of this evidence on their strength of conviction regarding the diagnosis of spinal stenosis. DESIGN: Prospective online survey. SETTING: University-based project. PARTICIPANTS: American physiatrists recruited by online postings and postcards. INTERVENTIONS: A recursive process presented a scenario that allowed clinicians to choose 1 of 10 clinical factors and then asked their level of certainty about diagnosis when that factor is true. Subsequent questions build on that assumption by adding other factors. MAIN OUTCOME MEASURES: Certainty regarding the diagnosis of clinical lumbar spinal stenosis. RESULTS: Of a total of 97 participants, 80 completed 3 or more iterations. "Leg pain while walking" (66%), "must sit down or bend" (66%), and "flex forward while walking" (49%) were the most commonly selected questions. "Normal foot pulses" (19%), "back pain" (16%), "leg pain" (15%), "relief with rest" (14%), and "sensory deficits" (12%) were of intermediate value, whereas "problems with balance," "have fallen recently," and "the sacroiliac joint is not the main pain generator" were all chosen less than 5% of the time. Statistically significant (P < .05) change in certainty ceased after 6 questions at 86.2% certainty. CONCLUSIONS: A recursive approach to diagnostic certainty is valuable. Within 5 questions, clinicians become almost 90% certain that a person has clinical spinal stenosis. This question set provides one pragmatic clinical criterion for the syndrome of lumbar spinal stenosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".