Bibliographic record
Abstract
Anesthesiology’s journal-based CME program is open to all readers. Members of the American Society of Anesthesiologists participate at a preferred rate, but you need not be an ASA member or a journal subscriber to take part in this CME activity.Please complete the following steps:The American Society of Anesthesiologists is approved by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing medical education programs for physicians.The American Society of Anesthesiologists designates this educational activity for a maximum of 1 AMA PRA Category 1 Credit ™. Physicians should only claim credit commensurate with the extent of their participation in the activity.Purpose: The focus of the journal-based CME program, and the articles chosen for the program, is to educate readers on current developments in the science and clinical practice of the specialty of Anesthesiology.Target Audience: Physicians and other medical professionals whose medical specialty is the practice of anesthesia.Learning Objectives: After reading this article, participants should have a better understanding of the pathogenesis, diagnosis, and treatment of lumbar zygapophysial (facet) joint pain.Authors – Steven P. Cohen, M.D., and Srinivasa N. Raja, M.D.Grants or research support: Dr. Cohen receives partial salary support from the John P. Murtha Neuroscience and Pain Institute, Johnstown, Pennsylvania, and the US Army. Dr. Raja has unrestricted grants from Allergan, Irvine, California, and Ortho-McNeil, Raritan, New Jersey, and serves as scientific advisor for Fralex Therapeutics, Toronto, Ontario, Canada. He receives salary support from grant No. NS-26363 from the National Institutes of Health, Bethesda, Maryland.Consultantships or honoraria: NoneQuestion Writers – Peter L. Bailey, M.D., and Leslie C. Jameson, M.D.Drs. Bailey and Jameson have no grants, research support, or consultant positions, nor do they receive any honoraria from outside sources, which may create conflicts of interest concerning this CME program.Based on the article by Cohen and Raja entitled “Pathogenesis, diagnosis, and treatment of lumbar zygapophysial (facet) joint pain” in the March issue of Anesthesiology, choose the one correct answer for each question:1. Which of the following descriptions of lumbar facet joints is the most accurate?A. They are not true synovial joints.B. Each joint contains approximately 1–1.5 ml of fluid.C. The fibrous capsule is arranged to provide maximum resistance to extension.D. The ligamentum flavum forms part of the capsule posteriorly.2. Which of the following mechanisms best explains the increased degeneration of neighboring facet joints when a single level of the lumbar spine is surgically fused?A. Increased facet joint motionB. Nerve root injury during surgeryC. Surgery-induced inflammationD. Loss of vascular supply3. Which of the following statements concerning lumbar facet joints is most likely true?A. They bear most of the axial load in the spine.B. Each has dual innervation from medial branches of the posterior primary rami at the same level and one level below the joint.C. They primarily serve a protective role by limiting movement in all planes.D. They all have the same anatomic orientation.4. Which of the following is the most sensitive and specific diagnostic test to identify lumbar facet inflammation as the source of low back pain?A. History of a torsional injuryB. Paraspinal tenderness to palpationC. Computed tomographyD. An effective response to local anesthetic block5. Which of the following statements concerning the pain pattern(s) associated with lumbar facet pain is most likely true?A. The synovium is the most likely pain generator.B. Upper, compared to lower, lumbar facets more commonly produce pain that is referred to the groin.C. Pain can be referred to below the knee.D. Pain is never radicular.6. Which of the following treatment options for lumbar facet pain is least likely to be successful?A. SurgeryB. Conservative therapiesC. Local anesthetic blocksD. Radiofrequency nerve ablation
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.923 | 0.849 |
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".