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Record W2587009144

Importance of bone marrow examination in cases of pancytopenia: A morphological study.

2016· article· en· W2587009144 on OpenAlexaff
Rumpa Das, Gorakh Nath

Bibliographic record

VenueAnnals of Pathology and Laboratory Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicHematological disorders and diagnostics
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsPancytopeniaMedicineBone marrowAplastic anemiaMegaloblastic anemiaBone marrow examinationBiopsyPathologyAnemiaInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: Pancytopenia is a pathological manifestation resulting from various disease processes affecting the bone marrow. Therefore, bone marrow examination is an important diagnostic tool to evaluate the underlying causes of pancytopenia. Methods: Present study was done in 64 cases fulfilling the criteria of pancytopenia over a period of two years. Bone marrow examination including bone marrow aspiration and bone marrow biopsy (only in cases of dry tap on aspiration) was performed in all the cases and morphological study along with cytochemical staining was done. The findings were correlated with peripheral blood examination. Diagnostic value of bone marrow examination in cases of pancytopenia was established. Result: 61 out of 64 cases were successfully diagnosed with the morphological examination of bone marrow. The most common cause of pancytopenia in the present study was megaloblastic anemia (57.81%) followed by aplastic anemia (18.75%) and acute leukemia (9.37%). Other causes of pancytopenia were dimorphic anemia due to mixed deficiency, lymphoma, multiple myeloma, infectious disease and storage disease. The diagnostic value of bone marrow examination in cases of pancytopenia in the present study was 95.31%. Conclusion: Morphological examination of bone marrow is an extremely helpful and specific diagnostic tool in cases of pancytopenia. Bone marrow aspiration and biopsy complement each other but diagnosis can solely be made in most of the cases by examining only the bone marrow aspiration smears.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.348
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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