Laboratory practices for manual blood film review: Results of an IQMH patterns of practice survey
Bibliographic record
Abstract
INTRODUCTION: Examination of a blood film is the second most common hematology test, after the complete blood count. Interpretation of a peripheral blood film by trained laboratory professionals provides valuable diagnostic information. The Institute for Quality Management in Healthcare (IQMH) Hematology Scientific Committee developed a questionnaire to gather information regarding current practices for manual blood film review and reporting from laboratories participating in IQMH Morphology proficiency testing (PT) surveys. METHODS: An online survey was distributed to 174 laboratories, 97% submitted results. RESULTS: Of the respondents, the majority (82%) indicated affiliation with small- or medium-sized hospitals (<500 beds). 80% of respondents had core laboratory technologists performing manual blood film reviews, while only 2% utilized dedicated hematology technologists with morphology expertise. All respondents had a policy for manual blood film review by a technologist, 70% did not have blood films reviewed by a senior/charge technologist prior to review by a physician. The majority (88%) of participants included morphological findings in their critical result list; of these, 98% include malaria and 88% include the first-time finding of blasts as critical results. 59% of participants indicated that they have a procedure in place to ensure that interpretation and confirmation of first-time potentially significant morphological findings are available from a physician at all times. CONCLUSION: This survey identified significant variation in blood film review and reporting practices across participating laboratories. The IQMH Hematology Scientific Committee will develop best practice recommendations to guide and standardize practice.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".