A benchmarking project on the quality of previous guidelines about the management of malignant pleural effusion from the European Society of Thoracic Surgeons (ESTS) Pleural Diseases Working Group
Bibliographic record
Abstract
OBJECTIVES: In the European Society of Thoracic Surgeons (ESTS) survey about management of malignant pleural effusions (MPE), 56% of respondents are not informed of any relevant clinical guidelines and 52%, who are aware of the existence of guidelines, declared that they are in need of updating or revision. The ESTS Pleural Diseases Working Group developed a benchmarking project on quality of previous guidelines on the management of MPE. METHODS: The Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument was used to assess each guideline. Each item was scored on a 7-point scale. Scores for each domain were calculated. Economic data for the nations which have issued the guidelines were collected from the Organisation for Economic Cooperation and Development health statistics database. RESULTS: Six guidelines fitted the inclusion criteria and were assessed. Five out of 6 guidelines were produced by a multinational collaboration. Observers would recommend only 2 guidelines with minimal modification. Two areas that received the best score were clarity of presentation and scope and purpose (objectives and health questions target population). The applicability of guideline domain had the lowest score. Multivariate analysis demonstrated that clarity of presentation, international guidelines and publication through medical journal were related to improved scores. A strong correlation was observed between the measures of economic status. CONCLUSIONS: The quality of guidelines assessed by the AGREE II criteria was found to be extremely variable. Guidelines achieving higher AGREE II scores were more likely to come from the European Union with the direct involvement of scientific societies in their development. It was also recognized that some fundamental unanswered questions remain about the management of MPE.
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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 | 0.078 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".