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Record W2564571195 · doi:10.5430/jst.v7n1p23

Effects of whole brain radiation on blood counts

2016· article· en· W2564571195 on OpenAlexvenueno aff
Kalvin Foo, Ashish Patel, G.K. Richards, Ben Goldsmith, Alan Turtz, Piya V. Saraiya, Robert A. Somer, Nati Lerman, H. Warren Goldman, Gregory J. Kubicek

Bibliographic record

VenueJournal of Solid Tumors · 2016
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUnivariate analysisAnemiaInternal medicineBone marrowRadiation therapyHemoglobinPlateletOncologyCancerStatistical analysisMultivariate analysisGastroenterologySurgery

Abstract

fetched live from OpenAlex

Background: Whole brain radiation therapy is commonly used in the treatment of patients with CNS metastatic disease. Radiation to other areas of the body is associated with decrease in bone marrow proliferation. It is unclear what the effects ofWBRT have on blood counts. Methods: Retrospective chart review of patients with brain metastases treated with WBRT with recorded hematologic valuesbefore and after treatment. Univariate analysis was performed to identify statistical differences in outcome via paired t -testing. Results: Forty-nine patients were analyzed. Median age was 61 and 36 subjects were female. Analysis revealed significantly amedian decrease of 0.87 g/dL in hemoglobin values ( p < .01) and 34 in platelet counts ( p < .01) after treatment, but no significantdecrease in WBC values ( p > .05). Conclusion: WBRT leads to a decrease in Hgb and platelets but does not appear to affect WBC counts. Physicians and patientsshould be aware of this side effect of WBRT.KeyWords: Whole brain radiotherapy, Anemia, Metastatic brain cancer

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.265
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Explore more

Same venueJournal of Solid TumorsSame topicBrain Metastases and TreatmentFrench-language works237,207