Quality of chronic pain interventional treatment guidelines from pain societies: Assessment with the AGREE II instrument
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Procedures to relieve pain are performed frequently but there are concerns about patient selection, appropriate image guidance, frequency and training for physicians. Patients, healthcare providers, policymakers and licensing bodies seek evidence-based recommendations to use these interventions judiciously. In this review we appraised the methodological quality of recent clinical practice guidelines (CPGs) for interventional pain procedures. DATABASE AND DATA TREATMENT: A systematic search of the medical literature was performed. Three trained appraisers independently evaluated the methodological quality of the CPGs using a validated instrument, the Appraisal of Guidelines in Research and Evaluation II (AGREE II). Six domains were considered: 1) score and purpose; 2) stakeholder involvement; 3) rigour of development; 4) clarity of presentation; 5) applicability and 6) editorial independence. A total of 23 items were scored. CPGs were deemed 'high quality' if a mean scaled score above 60% for rigour of development and for two other domains was obtained. RESULTS: Mean scaled domain quality scores ranged from 61.72% to 69.99%. Despite being based on modest levels of evidence, two of the four included CPGs were considered to be of high methodological quality. The AGREE II scores across the four guidelines exhibited good inter-rater reliability. None of the guidelines involved key stakeholders such as patients, other healthcare providers, and payers. CONCLUSIONS: All four CPGs were limited by a weak execution of the guideline development process. There is a need to develop methodologically sound evidence-based guidelines for the use of interventional pain procedures using a rigorous process that involves all relevant stakeholders. SIGNIFICANCE: This systematic review appraises the methodological quality of existing CPGs on interventional procedures using a validated epidemiological tool (AGREE II). The aims of this review were to identify methodological and knowledge gaps in existing CPGs. Findings of this study will help in development of a high-quality CPG that can assist healthcare providers and patients in making informed decisions while ensuring that the right intervention is performed for the right patient at the right time. The quality of the evidence provided by the CPGs provided in support of their recommendations was also evaluated.
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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 | 0.270 | 0.463 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.025 | 0.023 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier 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".