Early markers of occult megaloblastosis for low-cost detection of hyperhomocysteinemia in patients with ischaemic stroke: preventive approach for primary health care
Bibliographic record
Abstract
Recent studies have focussed on the association between elevated homocysteine levels with megaloblastic changes and thromboembolic events, but the relationship between occult megaloblastosis (with normal haemoglobin levels) and ischaemic stroke has not been widely explored. The objective of this study is to establish a simple and economical marker for the detection of occult megaloblastosis at the community health care level in developing countries. A hundred patients who met the inclusion criteria were studied. At the 5% level of significance, the levels of cobalamin and folate were significantly lower, while the number of hypersegmented neutrophils on the peripheral smear was higher in patients from Group A (70 patients with high homocysteine) compared with the patients in Group B (30 patients with normal homocysteine). Forty-five (64.2%) of the 70 patients in Group A showed hypersegmentation of neutrophils in the peripheral smear. The high cost and difficulty in performing the vitamin assays limit their use as early markers of megaloblastosis. Hence, we conclude that in developing countries, the detection of hypersegmented neutrophils can be used at the primary healthcare level for early diagnosis of occult megaloblastosis, so that early therapeutic interventions with vitamins can prevent attacks of hyperhomocysteinemia-induced ischaemic stroke.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".