Genetic hemoglobin disorders and anemia in Cambodian women of reproductive age (389.7)
Bibliographic record
Abstract
Anemia is common in Cambodian women of reproductive age. Anemia can lead to adverse pregnancy outcomes and other serious health consequences. Potential causes of anemia include micronutrient deficiencies, infection and disease. In Cambodia, genetic hemoglobin (Hb) disorders are common, leading to anemia and other complications. Objective: To examine associations between anemia (Hb <120g/L) and genetic Hb disorders in Cambodian women (18‐45 y). Methods: 450 women from Prey Veng province provided blood. A complete blood count was performed and the presence and typing of hemoglobin disorders was carried out by PCR and electrophoresis. Results: Overall, the prevalence of anemia in women was 33.1%, of which 61% was microcytic (Hb <120g/L and MCV <80fl). The prevalence of genetic hemoglobin disorders was over 55% (most commonly alpha‐thalassemia, Hb E and Hb CS) and were significantly correlated with anemia. Of women with anemia, over two‐thirds had an abnormal genetic hemoglobin type. Less than 5% of women had a low serum ferritin (< 15 µg/L). Conclusion: The majority of anemia in Cambodian women is microcytic anemia. A major predictor of anemia was genetic Hb disorders. Low serum ferritin was uncommon suggesting that iron deficiency is not a major problem. However, genetic Hb disorders may be confounding the interpretation of ferritin and leading to an underestimation of iron‐deficiency anemia. Other indicators of iron status and other micronutrients involved in anemia are being examined. Grant Funding Source : Supported by The International Development Research Centre and The Department of Foreign Affairs, Tr
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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".