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Record W1985909410 · doi:10.1097/mnm.0000000000000030

Deficiencies in product labelling instructions and quality control directions for 99mTc radiopharmaceuticals

2013· article· en· W1985909410 on OpenAlexaff
Federica Eleonora Buroni, Lorenzo Lodola, Marco Giovanni Persico, C. Aprile

Bibliographic record

VenueNuclear Medicine Communications · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadioactive Decay and Measurement Techniques
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsLabellingDocumentationQuality (philosophy)DirectiveProduct (mathematics)Computer scienceControl (management)VaguenessMedicineMedical physicsOperations managementMathematicsPsychologyEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the study was to identify deficiencies in product labelling instructions for reconstitution and in the quality control directions detailed in the technical leaflets (TLs) or summary product characteristic (SPC) sheets of commonly used technetium labelling cold kits. MATERIALS AND METHODS: The reconstitution and quality control directions in 25 TLs/SPCs were evaluated to identify deficiencies, incompleteness, restrictions, errors, impracticability, and vagueness. In addition, their congruence with the statements given in the relative European Pharmacopoeia (Ph. Eur. VII ed.) monography and diagnostic reference levels of Directive 97/43/EURATOM was evaluated. RESULTS: Deficiencies in information were scored and classified into five categories: 1, absent or incomplete; 2, restrictive; 3, inconsistent or wrong; 4, impractical; and 5, vague. In the 25 documents analyzed a total of 141 deficiencies were found (corresponding to 40.2% of the total scores assigned), and more frequently they pertained to quality control procedures (70.9%), followed by those related to quantitative composition (14.9%), preparation (8.5%), and particle size (5.7%). Nearly 80% of these deficiencies were classified as type 1 - that is, absent or incomplete information. CONCLUSION: The indications in TLs and SPCs should provide useful information for maintaining the quality and purity of the radiopharmaceutical preparation and ensure the safety level and effectiveness required by law. However, the instructions are often suboptimal or even erroneous, and consequently there are countless failures or difficulties, which represent an impediment to good laboratory practice. We believe that a 'smart' review of radiopharmaceutical documentation would be beneficial in order to align these indications to the real needs of the operators involved in routine in-house nuclear medicine practice.

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)0.042
metaresearch head score (Gemma)0.100
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 score0.042
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.100
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.100
GPT teacher head0.367
Teacher spread0.267 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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