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Record W3128429095 · doi:10.47391/jpma.533

Sickle hemoglobin: How critical are laboratory quality measures for accurate identification?

2021· article· en· W3128429095 on OpenAlexaboutno aff
Nazish Sana, Muhammad Shariq Shaikh, Admin Admin

Bibliographic record

VenueJournal of the Pakistan Medical Association · 2021
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSickle cell traitHemoglobinHemoglobinopathyPolymerase chain reactionAsymptomaticThalassemiaPopulationGlobinFetal hemoglobinGenetic counselingMutationHemoglobin variantsBeta thalassemiaGeneticsDiseaseGeneInternal medicineBiologyFetus

Abstract

fetched live from OpenAlex

Madam, Adult haemoglobin (Hb) comprises of 2 alpha and 2 beta-globin chains, each having a haem molecule attached. In healthy individuals, around 95-98% HbA (?2?2) and 2–3.5% of Hb A2 (?2?2) are present. The genetic defect of globin chain in which valine is replaced for glutamic acid at position 6 of ? globin chain results in sickle haemoglobin (HbS). Homozygous genetic defect (?S?S) results in a symptomatic disease called 'sickle cell anaemia' whereas, heterozygous (??S) state is asymptomatic and commonly called as "sickle cell trait' [1]. On deoxygenation and dehydration, HbS undergoes irreversible polymerization causing deleterious effects in vivo [2]. Around 3.2 million people have sickle-cell disease worldwide, with about 80% cases in Africa. About 0.5 to 1 per cent of the Pakistani population carries HbS3. Currently, high-performance liquid chromatography (HPLC) is the preferred method in which HbS elutes at retention time ranging in between 4.1 to 4.7 minutes. Several other variant haemoglobins cause interference by co-eluting at same retention time include HbA2, Hb Q-Thailand, Hb Manitoba, Hb Russ, Hb Stanlivelly-II, HbE- Saskatoon, Hb Montgomery and many more[4]. Therefore, it is difficult to identify and differentiate HbS precisely from interfering variant haemoglobins for proper diagnosis and future genetic counselling of patients. The definitive test for this purpose is molecular detection of underlying mutation either by polymerase chain reaction (PCR) or sequencing of the beta-globin gene. Molecular tests, however, are expensive and require expertise. Therefore, these tests are not widely available in Pakistan and other resource constraint countries. World's leading quality assurance organizations such as College of American Pathologists (CAP) recommend that all cases found HbS positive in the primary screening should be confirmed by secondary testing [5], this can easily be achieved by sickling test. In the sickling test, the sample is combined with reducing agent (Sodium Met bisulfate) resulting in red cell hypoxia. Cells with HbS change to sickle shape from their normal biconcave shape, diagnosed by microscopic examination along with controls. This cost-effective and readily available technique helps to differentiate HbS from other variants. Therefore, every laboratory should confirm the presence of HbS by sickling test, and the government should ensure the availability of molecular tests at the mass level at a reduced cost supported by the efficient health insurance system. The impact of these strategies will provide accurate and timely diagnosis, Continuous...

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)0.004
metaresearch head score (Gemma)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.638
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.037
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 integrity0.0000.001
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 head0.018
GPT teacher head0.342
Teacher spread0.323 · 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.

Study designNot applicable
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
Published2021
Admission routes1
Has abstractyes

Explore more

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