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An Operational Definition of Cobalamin Replacement Based upon Administrative Health Data.

2004· article· en· W2555608740 on OpenAlexaffabout
David Szwajcer, William D. Leslie, A. Majid Shojania, Marina Yogendran, Colleen Metge

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsManitoba HealthUniversity of Manitoba
Fundersnot available
KeywordsMedicineMedical prescriptionAnemiaPediatricsVitamin B12CobalaminEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: A large clinical dataset of vitamin B12 measurements (over 12,000 patients) and Schilling tests (over 700 patients) has been assembled from participating Manitoba laboratories (1995–2000) in order to assess clinical outcomes (as defined from administrative health data) in relation to tests of cobalamin [Cbl] deficiency. In order to control for Cbl replacement, it is necessary to confirm that Cbl replacement can be accurately determined from administrative data sources such as the Drug Program Information Network (DPIN) and/or medical claims for therapeutic injections. DPIN is known to be reliable for oral prescription drugs, but parenteral Cbl may be more difficult to identify and non-prescription oral Cbl would not be recorded. We believe that the preferred route of Cbl administration in Manitoba was parenteral during 1995–2000, but this needs to be confirmed. Methods: Cases (expected to have a high likelihood for Cbl replacement) consisted of all adult hospital discharges between 1995 and 2000 with a diagnosis of pernicious anemia or other Cbl deficiency anemia (ICD-9-CM 281.0, 281.1) who survived for at least one year post-discharge without personal care home admission (n=388). Matched controls (3 controls for each case) with a low likelihood for Cbl replacement were similarly defined from hospital discharges without any ICD-9-CM neurologic or haematologic diagnosis (n=1,164). Controls were matched with cases for gender, birth year and hospitalization year. For each case and control the number of Cbl dispensations (ATC code B03BA01) and therapeutic injections (tariff code #8954) were tabulated during the first three years post-discharge. Sensitivities (fraction of cases receiving Cbl replacement) and specificities (fraction of controls not receiving Cbl replacement) were calculated for different cutoffs of Cbl dispensations, therapeutic injections and combinations according to year of diagnosis (YOD) and overall. Weighted linear regression between YOD and sensitivity was performed to look for an effect of recent oral Cbl replacement. Results: Sensitivity for the a priori operational definition (≥2 Cbl dispensations) was 0.59±0.02 with specificity 0.96±0.01. Using one or more Cbl dispensations improved sensitivity to 0.71±0.02 with similar specificity of 0.95±0.01. Therapeutic injections alone were less useful (≥1 injection sensitivity of 0.65±0.02 with specificity of 0.92±0.01, ≥2 injections sensitivity of 0.61±0.02 with specificity of 0.95±0.01). The combination that maximized sensitivity + specificity was ≥1 dispensation or ≥2 therapeutic injections (sensitivity 0.80±0.02, specificity 0.93±0.01). Sensitivity measurements did not show any significant relationship with YOD. Conclusions: The optimal definition for Cbl therapy based upon administrative health data appears to be at least one Cbl dispensation identified in the DPIN database or at least two therapeutic injections identified from medical claims. In assessing clinical outcomes in relation to Cbl testing and replacement, we propose to validate findings derived with the primary combined definition through secondary analyses using independent definitions of Cbl replacement (≥1 dispensation alone or ≥2 therapeutic injections alone). Overall sensitivity was lower than expected but may reflect that some cases are not prescribed Cbl replacement post-discharge. Sensitivity was unrelated to YOD arguing against oral Cbl replacement as the explanation.

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)0.006
metaresearch head score (Gemma)0.016
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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.405
Teacher spread0.277 · 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

Citations0
Published2004
Admission routes2
Has abstractyes

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