The use of a modified Delphi technique to develop a critical appraisal tool for clinical pharmacokinetic studies
Bibliographic record
Abstract
BACKGROUND: Critical appraisal aids in assessing the quality of scientific literature, which is central to the practice of evidence-based medicine. Several tools and guidelines are available for critiquing and assessing the quality of specific study types. However, limited guidance exists for critical appraisal of clinical pharmacokinetic studies. AIM: We aimed to achieve experts' consensus regarding the quality markers for clinical pharmacokinetic studies in an attempt to develop a critical appraisal tool. METHOD: Quality markers related to clinical pharmacokinetic studies, were derived from the published literature and categorized according to manuscript reporting domains (abstract, introduction/background, methodology, results, discussion, and conclusion). Questions that aid in appraising pharmacokinetic studies were formulated from these quality markers. Experts were involved in a modified Delphi process to achieve a consensus regarding the formulated questions. The proposed tool was pilot tested on 30 recently published clinical pharmacokinetic studies. Inter-observer agreement was measured to determine the reliability of the included items. RESULTS: Twenty-five experts consented to participate. Three rounds of a modified Delphi survey were required to generate a consensus for a 21-item tool aimed at appraising the quality of clinical pharmacokinetic studies. When applied to 30 recently published clinical pharmacokinetic studies, most items scored fair to moderate levels of agreement (61.90-95.24%). CONCLUSION: The clinical pharmacokinetic critical appraisal tool (CACPK) developed in this study consisted of 21 items aimed at helping an end-user to determine the quality of a pharmacokinetic study. Further studies are warranted to reaffirm the validity and reliability of the CACPK tool.
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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 | 0.278 | 0.339 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.019 | 0.009 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".