Practice Guidelines on the Reporting of Smudge Cells in the White Blood Cell Differential Count
Bibliographic record
Abstract
Smudge cells are a well-described artifact in hematologic morphology that result from the rupture of fragile lymphocytes secondary to the process of making the peripheral blood film (Figure). Although seen in both reactive and malignant lymphocytosis, they are more often associated with the lymphoproliferative disorders, as the total lymphocyte counts are usually higher and there may be acquired membrane defects in these disorders. The issue of either including these “cells” in the standard manual white blood cell differential count or enumerating them separately as a proportion of a total differential cell count has rarely been examined in the literature, as evidenced by the dearth of articles on the subject in the MEDLINE database. Smudge cells are counted accurately as lymphocytes by modern blood cell analyzers, which commonly enumerate 10 000 white cells or more in a 5-cell differential count. The issue is clinically significant when comparisons are made between the manual differential counts and the automated differential counts performed to monitor the lymphocyte doubling time, which has been promoted as a prognostic factor in disease progression in chronic lymphocytic leukemia.1 The smudge cells on the film will not be included in the manual differential, thereby resulting in an undercounting of the actual lymphocytes present and an overstating of the neutrophil count relative to the automated count, the “true count.”The Quality Management Program—Laboratory Services (QMP-LS), a joint initiative of the Ontario Medical Association and the Ontario Ministry of Health and Long-Term Care, administers an external quality assessment program including periodic hematologic check samples for all licensed laboratories in Ontario. Participants often include smudge cells separately from the manual differential count, with a resultant discrepancy with the automated differential count. A Good Practice Guideline concerning the reporting of smudge cells has recently been issued.2 This guideline recommends reporting an automated differential count (even with suspect flags) with an associated qualitative comment that smudge cells are present. If an automated count is unavailable, smudge cells should be counted as lymphocytes with an associated qualitative comment, or as a separate category within the total differential cell count.As QMP-LS communicates with every licensed laboratory in the province of Ontario, we expect that the application of this guideline will lead to a standard pattern of practice for the reporting of smudge cells. This will avoid discrepancies when interchanging the use of automated or manual leukocyte differential cell counts, which could possibly cause confusion among clinicians when following the lymphocyte doubling time as a prognostic factor in chronic lymphocytic leukemia.
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 | 0.075 | 0.286 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.015 |
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".