Evidence map›Paper›PMID 41342164›Full record

ReviewHaematologica2026

The evolution of the complete blood count: have we gone too far?

Marshall A Lichtman, Richard W Burack

Abstract readHistorical ArticleReview
In one paragraph

Review in Haematologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Marshall A LichtmanDepartment of Medicine and the James P. Wilmot Cancer Institute, University of Rochester Medical Center, Rochester. marshall_lichtman@urmc.rochester.edu.
Richard W BurackDepartment of Pathology and James P. Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The complete blood count (CBC) began its evolution at the end of the 19th century with the development of the hemacytometer to count blood cells. Soon thereafter, the hematocrit, a method to determine the packed red cell volume, was described in Sweden. Subsequently, the mean volume and hemoglobin content of red cells were added. Stains that distinguished individual leukocyte types permitted differential white cell counts: the product of the total white cell count and the fraction of each white cell type. A reliable means to count platelets rounded out the manual CBC. In 1954, Wallace Coulter introduced the Model A electronic particle counter. Modifications and advancements evolved into the Model S, a rapid, accurate, electronic method to determine the standard variables in the CBC and an array of additional measurements. Electronic particle counting has undergone numerous further developments including the application of florescence technology, such that approximately 30 variables can be measured as part of a CBC. This evolution has led to a chaotic situation; a recent study showed that the CBC ranged from 12 to over 24 variables when measured in either a community or academic hospital hematology laboratory. Out-of-range values, frequent and often trivial, have to be reconciled for patient and physician. Redundant and very low value variables have accrued in the CBC. We propose a major change in the CBC depending on the reason for its measurement. These recommendations markedly decrease the variables measured and make the results more impactful, which will enhance the physician's focus on the use of this key laboratory test to the benefit of the patient's care.

Indexed as

Blood Cell CountHematocritHistory, 19th CenturyHistory, 20th CenturyHistory, 21st CenturyHumans

Identifiers

PMID41342164
PMCPMC13040180

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.