Assessment of the Platelet Parameters in Children With Type 1 Diabetes Mellitus
Bibliographic record
Abstract
Background: The purpose of this study was to assess platelet morphological parameters in children and adolescents with type 1 diabetes mellitus (T1DM) and to determine the factors affecting those parameters. Methods: A total of 80 children with type 1 diabetes mellitus and 80 healthy control subjects were included in this study. All subjects’ platelet parameters including platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT) levels were measured. Age at diagnosis, duration of diabetes, and hemoglobin A1c (HbA1c) levels of patients with T1DM were also recorded. Results: There was no significant difference in PLT, MPV, PDW and PCT values between patients and controls (P > 0.05). PCT and PLT values were higher in patients with poor metabolic control compared to the other cases (P = 0.002, P = 0.005). Positive correlation was found between HbA1c and PCT (r = 0.28, P = 0.01). There was no correlation between HbA1c and MPV, PDW and PLT. Conclusions: Indices of platelet morphology such as PCT, PLT, PDW and MPV were similar in children with T1DM and in healthy controls. However, an increase in PCT values in poor glycemic control group and a significant positive correlation between PCT and HbA1c were observed, suggesting that PCT levels may be an early marker of vascular complication. J Endocrinol Metab. 2018;8(6):144-148 doi: https://doi.org/10.14740/jem537
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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 | 0.001 | 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 | 0.001 |
| 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".