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Record W3022373814

Neonatal screening of inborn errors of metabolism using tandem mass spectrometry: an evidence-based analysis.

2003· article· en· W3022373814 on OpenAlexaboutno aff
Medical Advisory Secretariat

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsNewborn screeningCongenital hypothyroidismMedicineInborn error of metabolismPediatricsDried bloodTandem mass spectrometryDried blood spotMass spectrometryChemistryInternal medicineChromatography
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES AND METHOD: The Medical Advisory Secretariat undertook a review of the evidence on the effectiveness and cost-effectiveness of using tandem mass spectrometer [MS/MS] for the neonatal screening of inborn errors of metabolism [IEM]. The review is based on two systematic reviews commissioned by the National Health Services (United Kingdom) and relevant research literature that was published after the completion of these two systematic reviews. A horizon scanning was conducted to determine the current status of neonatal screening programs in other national and international jurisdictions. The MAS also consulted with stakeholders including the laboratory branch, an expert in IEM at a pediatric hospital, MS/MS experts and a MS/MS manufacturer. RESULT: Synthesis of information obtained from the above process showed that: Ontario is currently screening all newborns for phenylketonuria [PKU] and congenital hypothyroidism [CH] using the Guthrie method on dry blood spots obtained by heel prick before discharge from hospital.MS/MS can detect 25 IEMs in a single process on the same dry blood spot.Computer algorithms have been used to automate the MS/MS screening process to provide rapid throughputs of 400 samples or more per day. Screening for additional IEMs using MS/MS does not add significant cost to the program.MS/MS -based neonatal screening showed sensitivity of 100% and specificity of 83% to 99% depending on the IEM. The specificity of MS/MS in detecting PKU is significantly superior to that of the current Guthrie method and is therefore able to reduce the number of false positive results.For certain inborn errors of metabolism not currently screened, early detection and simple treatment could avoid early mortality and prevent or reduce mental retardationUsing eligibility criteria recommended by the World Health Organization adapted to Ontario, a rating system was developed and applied to assess the IEMs recommended for inclusion in neonatal screening.The assessment showed that PKU and CH should continued to be screened. In addition, medium chain acyl-CoA dehydrogenase deficiency [MCADD] and congenital adrenal hyperplasia [CAH] met most of the criteria for inclusion in a neonatal screening program. MCADD can be screened with PKU by MS/MS while the test for CAH requires a different methodology.An expanded neonatal program would require an enhanced infrastructure for result interpretation, reporting, care provision and counseling.Important ethical and societal issues including informed consent need to be addressed.As of 1998, twenty-six states in the United States were using MS/MS for newborn screening of IEMs. In Canada, British Columbia, Saskatchewan and Nova Scotia use MS/MS for IEM related assays. Manitoba is planning to implement MS/MS -based neonatal screening in 2003.Among Canadian jurisdictions, British Columbia, Manitoba, Quebec, Nova Scotia and Saskatchewan are screening for more IEMs than Ontario.

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)0.016
metaresearch head score (Gemma)0.046
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0100.008
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.260
Teacher spread0.225 · 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

Citations10
Published2003
Admission routes1
Has abstractyes

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