Report on the International Society for Laboratory Hematology Survey on guidelines to support clinical hematology laboratory practice
Bibliographic record
Abstract
INTRODUCTION: Given the importance of evidence-based guidelines in health care, we surveyed the laboratory hematology community to determine their opinions on guideline development and their experience and interest in developing clinical hematology laboratory practice guidelines. METHODS: The study was conducted using an online survey, distributed to members of the International Society for Laboratory Hematology (ISLH) in 2015, with analysis of collected, anonymized responses. RESULTS: A total of 245 individuals participated. Most worked in clinical and/or research laboratories (83%) or industry (11%). 42% felt there were gaps in current guidelines. The majority (58%) recommended that ISLH engages its membership in guideline development. Participants differed in their familiarity with, and use of, different organizations' guidelines. Participants felt it was important to follow best practice recommendations on guideline development, including engagement of experts, statement about conflict of interests and how they were managed, systematic review and grading evidence for recommendations, identifying recommendations lacking evidence or consensus, and public input and peer review of the guideline. Moreover, it was considered important to provide guidelines free of charge. Industry involvement in guidelines was considered less important. CONCLUSIONS: The clinical laboratory hematology community has high expectations of laboratory practice guidelines that are consistent with recent recommendations on evidence-based guideline development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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; 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".