Diagnosis of Hypoglycemia due to Over-Dosage of Insulin Analog, Insulin Lispro
Bibliographic record
Abstract
Serum insulin assay is used for the diagnosis of diabetes and hypoglycemia and is also used to quantify insulin for insulin pharmacokinetic evaluations. Serum C-peptide is usually measured in subjects who use insulin for evaluation of intrinsic insulin secretion. We experienced a hypoglycemic diabetic patient treated by premixed insulin lispro 75/25 (75% insulin lispro protamine suspension and 25% insulin lispro) who showed undetected serum levels of both insulin and Cpeptide. A 74-year-old type 2 diabetic man has been treated by injection of 26 units of premixed insulin lispro 75/25 before breakfast. In December 2010, his food intake decreased due to appetite loss, however, he injected 26 units of premixed insulin lispro 75/25, and subsequently developed disturbance of consciousness. He was admitted to our department, and his blood glucose level was 37 mg/dL. His consciousness promptly recovered after intravenous injection of glucose, and then he has been diagnosed as having hypoglycemia. We expected that his serum insulin level is high. However, serum insulin and also C-peptide were not detected. HbA1c is 5.5%, and anti-glutamic acid decarboxylase antibody was negative, and 125I-insulin binding rate was not too high (2.6%). His urinary C-peptide level was very low (4.0 μg/ day; normal range, 29.2 167.0 μg/day), suggesting the presence of severely decreased insulin secretion capacity. What is the cause of his hypoglycemia? Insulin analogs that are prepared with recombinant DNA technology are available for clinical use. One obvious question with insulin analogs is whether they are detectable by immunoassay. Serum insulin could not be detected by the chemiluminescent enzyme immunoassay (CLEIA) using Lumipulse Presto Insulin (Fuji Rebio, Tokyo, Japan) in our patient (Table 1). However, serum insulin could be measured by radioimmunoassay (RIA) using Insulin Eiken (Eiken Chemical Company, Tokyo, Japan). Lumipulse Presto Insulin could detect NPH human insulin, but, could not detect insulin lispro, and showed very low cross-reactivity with premixed insulin lispro 75/25 (Table 1). Insulin Eiken showed a high cross-reactivity with NPH human insulin, insulin lispro and premixed insulin lispro 75/25 (Table 1). Insulin lispro is a human insulin analog created by reversing the amino acids at positions 28 (Pro to Lys) and 29 (Lys to Pro) of the B chain of human insulin [1]. A sensitive RIA that is specific for insulin lispro has been developed [2]. Further, the combination of insulin assays that detect human insulin only or both human insulin and insulin analogs provides a new tool for studying pharmacokinetics of insulin lispro [3]. However, all of these assays are used mainly for research and are not usually used in clinical laboratories. Owen WE, et al studied cross-reactivity of insulin analogs with commercial insulin immunoassays [4]. Insulin lispro had a high cross-reactivity of 80% and 90% with the Access analyzer (Beckman Coulter) and the Advia Centaur analyzer (Bayer Diagnostics), respectively, whereas insulin lispro had a low cross-reactivity of 43% and 28% with the Coat-ACount (Diagnostic Products Corporation) and the IMMULITE 2000 analyzer (Diagnostics Products Corporation), respectively. The E170 method did not detect insulin lispro, indicating that the antibody used in this assay could not recognize an epitope that includes B28 and/or B29 of the B chain. The antibody in the assay of Lumipulse Presto InsuManuscript accepted for publication April 6, 2012
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".