Morphology and Chromic Status of Red Blood Cells Are Significantly Influenced by Gestational Diabetes
Bibliographic record
Abstract
BACKGROUND: The study shows the effect of hyperglycemia on RBCs in terms of morphological changes and their chromic status in women with gestational diabetes mellitus (GDM). METHODS: A total of 100 pregnant women were enrolled from Maternity and Children Hospital, Qassim, Saudi Arabia including 40 women with confirmed GDM (group-1), 30 women with either type 1 or type 2 diabetes (group-2) and 30 women with normal pregnancy without GDM or pre-gestational diabetes (control group-3). Demographic, anthropometric, medical and biochemical data were obtained from the study subjects. Complete blood count (CBC) and peripheral smears were performed from routine blood samples. Red blood cells (RBCs) morphological analysis was carried out by a hematologist and deviations in size, shape, and staining properties of the RBCs were recorded. RESULTS: The groups were similar in demographic characteristics (P > 0.05). RBCs showed normocytic and normochromic features in 83.3% patients of group-3 as compared to 57.5% in group-1, 30% in group-2, respectively. Microcytic hypochromic cells and anisocytosis were mostly encountered in group-2 in 53.3% and 93.3% patients respectively (P = 0.000). Forty percent of RBCs in goup-1 showed microcytic and hypochromic characteristics as compared to group-3 (P = 0.015). Additionally, 42.5% group-1 patients had anisocytosis as compared to group-3 (P = 0.003). Poikilocytosis, target cells and macrocytes were mostly observed in group-2. CONCLUSIONS: Persistent hyperglycemia changes shape, size and hemoglobin contents of RBCs which are associated with the hyperglycemic status and exposure time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".