Clinical laboratory values during diabetic pregnancies.
Bibliographic record
Abstract
BACKGROUND: Physiological pregnancy can affect routine laboratory tests, e.g., the erythrocyte sedimentation rate increases above the reference range for healthy non-pregnant adults and little is known about whether diabetes and pregnancy together can cause additional changes that require monitoring of blood-tests. OBJECTIVE: The purpose of this study was to investigate changes in clinical chemistry and haematological laboratory test results during pregnancies of type 1 diabetics and to compare the results with changes during normal pregnancies. METHODS: We studied 25 type 1 diabetic women with standard clinical chemistry and haematological blood-tests during pregnancy. RESULTS: Haemoglobin, haematocrit, and erythrocyte number decreased until the 3rd trimester and leucocytes and platelets did not change significantly. The erythrocyte sedimentation rate increased by over 200%. Protein and albumin decreased until the 3rd trimester to below the reference range. Urea did not change, creatinine decreased and uric acid increased within the reference range. AST and ALT remained within the reference range. Alkaline phosphatase and leucine aminopeptidase increased until above the reference range. Cholesterol and triglycerides increased until the third trimester above results from normal pregnancies. CONCLUSION: A wide range of biochemistry and haematology laboratory values changed during diabetic pregnancy comparable to physiological pregnancies. No additional routine laboratory-testing during diabetic pregnancies compared with physiological pregnancies is required.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 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".