Prevalence of α-Globin Gene Deletions Among Patients with Unexplained Microcytosis in a North-American Population
Bibliographic record
Abstract
Increasing multi-ethnicity is likely to make alpha-thalassemia (alpha-thal) more prevalent in Western metropolitan areas. Multiplex polymerase chain reaction (m-PCR) allows rapid and precise identification of most of alpha-thal carriers. With this method, we sought to determine the prevalence of alpha-thal and the corresponding genotype, among all non repetitive consecutive blood samples that had an unexplained microcytosis. These specimens had been sent to the hematology laboratory for a blood count analysis, found to be microcytic, and secondarily tested for ferritin level and hemoglobin (Hb) high performance liquid chromatography (HPLC) profile. Five hundred and sixteen microcytic blood samples were evaluated and 197 samples with normal ferritin and Hb HPLC were studied by m-PCR. Among 196 interpretable PCRs, 48 alpha-thal cases (24.5%) were identified: 28 with a single alpha-globin gene deletion and 20 with two alpha-globin gene deletions. Of these 20 cases, six showed two deletions in cis. None of the erythrocytic parameters studied predicted the presence of alpha-thal deletions. We conclude that a significant proportion (24.5%) of blood counts with microcytosis not explained by an iron deficiency, an inflammatory state or an abnormal Hb on HPLC, are caused by an alpha-globin gene deletion. The pertinence of genetic counseling for alpha-thal based on molecular diagnosis should be evaluated more formally in urban centers where this genetic condition is likely to have an increasing prevalence and clinical relevance.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".