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Record W2405522361

Prediction of anemia on unenhanced computed tomography of the thorax.

2003· article· en· W2405522361 on OpenAlexaff
Michelle Foster, Robert L. Nolan, Miu Lam

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsKingston General Hospital
Fundersnot available
KeywordsInterventricular septumMedicineHounsfield scaleAnemiaThorax (insect anatomy)HemoglobinIntracardiac injectionHematocritRadiologyCardiologyInternal medicineComputed tomographyAnatomyVentricle
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine if anemia can be predicted on unenhanced computed tomography (CT) of the thorax. METHODS: Hemoglobin and hematocrit levels were obtained within 24 hours of the unenhanced CT scan of the thorax of 200 patients. Anemia was defined as a hemoglobin level less than 140 g/L for men and less than 120 g/L for women. Regions of interest were placed on the left ventricular cavity, aorta and the interventricular septum if visualized. The attenuation of the interventricular septum and left ventricular cavity were correlated with the presence or absence of anemia. RESULTS: When the interventricular septum was not visualized, for every 1 Hounsfield unit (HU) increase in left ventricular attenuation, hemoglobin increased by 0.435 g/L (SE = 0.253, p < 0.001). Failure to visualize the interventricular septum did not exclude the presence of anemia in either sex. When the interventricular septum was visualized, 100% of males and 89% of females met the criteria for the diagnosis of anemia. The prediction of anemia by visualization of the interventricular septum alone yielded a sensitivity of 75.4% and a specificity of 90.3%, with 80% of patients correctly predicted. The multiple regression analysis model yielded a sensitivity of 94.2% and a specificity of 67.7%, with 86% of patients correctly predicted. CONCLUSION: The diagnosis of anemia should be suggested whenever the interventricular septum is visualized on unenhanced CT.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.209
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.224
Teacher spread0.199 · 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

Citations36
Published2003
Admission routes1
Has abstractyes

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