The use of serial outpatient complete blood count (<scp>CBC</scp>) results to derive biologic variation: a new tool to gauge the acceptability of hematology testing
Bibliographic record
Abstract
INTRODUCTION: Most estimates of biologic variation (sb ) are based on periodically acquiring and storing specimens from reference subjects, followed by analysis within a tightly controlled analytic run. We demonstrate that reliable estimates of sb can be derived for virtually all constituents of the CBC from previously obtained paired patient results and summary QC data. METHODS: A laboratory data repository provided all of the outpatient CBC results measured over 20.5 months at a large Canadian referral laboratory. These CBC measurements were taken on one of four Beckman Coulter LH analyzers. A total of 1852 different patients had CBCs repeated at least twice within 84 h. We tabulated the pairs of intrapatient constituents that were separated by 0-6, 6-12, 12-18,… 72-78, and 78-84 h. The standard deviations of duplicates (SDD) of the paired data were then regressed against time. The y-intercept represents the sum of sb and short-term analytic variation (sa ): y0 =(s(2) a +s(2) b )(1/2) . The short-term imprecision was determined from normal range Coulter quality control specimens. RESULTS: Patient sb for hematocrit, MCH, absolute monocytes, and absolute neutrophils are extremely close to those determined by biologic variation experiments using healthy volunteers. Most of the other estimates of sb tended to be slightly lower than literature estimates. CONCLUSIONS: We describe a novel approach to deriving sb . The ratio of the sb to sa (a measure of sigma) indicates that the Beckman Coulter LH is extremely suitable for CBC monitoring of outpatients as well as for inpatients, whose sb is generally higher.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".