A hyperglycaemic hyperosmolar state in a young child: diagnostic insights from a quantitative analysis
Bibliographic record
Abstract
This teaching exercise demonstrates how the application of principles of physiology can identify the cause of a severe degree of hyperglycaemia (plasma glucose concentration 80 mmol/l) in a very young patient with newly diagnosed diabetes mellitus, determine whether the patient has diabetic ketoacidosis, and highlight the potential risks for this patient on admission and during initial therapy. A consultation with Professor McCance was sought to determine whether this patient had an unusual degree of 'insulin resistance'. There were also uncertainties regarding the acid-base diagnosis. The patient did not appear to have an important degree of metabolic acidosis as judged from his pH of 7.39 and plasma bicarbonate concentration of 20 mmol/l in arterial blood; hence the diagnostic impression was that he had a hyperglycaemic hyperosmolar state. However, his plasma anion gap was significantly elevated, and remained so for 60 h, despite the administration of insulin. Issues in management concerning the basis for this severe degree of hyperglycaemia and how to minimize the risk of developing cerebral oedema are addressed. The missing links in this interesting story emerge during a discussion between the medical team and their mentor, Professor McCance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".