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Record W3090371684 · doi:10.1542/pir.2018-0279

A 4 year-old Girl with Diabetic Ketoacidosis and Lipemic Blood

2020· article· en· W3090371684 on OpenAlexaff
Chris Novak, Sarah J. Johnson, Graeme Rinholm, Jessica L. Foulds

Bibliographic record

VenuePediatrics in Review · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDiabetic ketoacidosisPolyuriaPolydipsiaHypertriglyceridemiaPancreatitisHyperlipidemiaKetoacidosisInternal medicineDiabetes mellitusGastroenterologyInsulinAcute pancreatitisPhysical examinationTriglycerideType 1 diabetesEndocrinologySurgeryCholesterol

Abstract

fetched live from OpenAlex

A 4-year-old previously healthy girl presents to the emergency department with a 1-month history of vague abdominal pain, constipation, and a 5.5-lb (2.5 kg) weight loss. She then developed polydipsia, polyuria, and fatigue for 1 week. There were no infectious or neurologic symptoms. On examination she had dry mucous membranes and a nontender abdomen without hepatomegaly. Initial investigations were diagnostic for diabetic ketoacidosis (DKA) with a blood glucose of 901 mg/dL (50 mmol/L), serum pH of 7.28, and a bicarbonate of 11.9 mEq/L (mmol/L). However, it was noted that the blood specimen was profoundly lipemic. The patient was admitted to the hospital for management of DKA and investigation for lipemia.Due to difficulty processing the sample, serum lipids levels were not accurately measured for 3 days, but the first available measurement showed a serum triglyceride of 5,938 mg/dL (67.1 mmol/L) and a total cholesterol of 1,227 mg/dL (13.87 mmol/L). There was a strong family history of autoimmunity and thyroid disease, but no significant early cardiovascular disease or hyperlipidemia. She had a typical diet, no prior medications, and no physical manifestations of hyperlipidemia including xanthelasma or cutaneous xanthomas. The patient received the standard hospital treatment protocol for DKA, but it was noted her hyperglycemia appeared slow to resolve despite ongoing intravenous fluid resuscitation following DKA resolution. She did not develop pancreatitis, and her lipid levels rapidly decreased following insulin therapy.Severe hypertriglyceridemia (HTG) has been defined as a serum triglyceride level of greater than 886 mg/dL (10 mmol/L), whereas extreme HTG is greater than 2,000 mg/dL (22.6 mmol/L). (1)(2) Extreme HTG can be due to genetic disorders of lipid metabolism; however, the majority of cases are secondary to other diseases or medications. A 2018 study of 36 children with extreme HTG found that only 14% had genetic disorders of lipid metabolism. The most common cause of extreme HTG was poorly controlled diabetes mellitus (30%), followed by the use of L-asparaginase and steroids in chemotherapy (28%), and calcineurin inhibitors postsolid organ transplant (14%). (1) There are also case reports of extreme HTG secondary to end-stage renal disease, uncontrolled hypothyroidism, and other medications such as human immunodeficiency virus antiretrovirals and propofol. (1) Secondary HTG is typically transient once the inciting cause is removed. It is important to consider genetic disorders of lipid metabolism in patients with a significant family history of early cardiovascular events and hyperlipidemia, or in children with persistently abnormal serum lipids. (3) These patients may require referral to pediatric endocrinology and genetic evaluation. It is thought that some patients who develop severe HTG may have a genetic predisposition leading to a dramatic response to a secondary cause. (1)Patients in DKA develop increased lipolysis due to increased counterregulatory hormones such as catecholamines, cortisol, and glucagon in an insulin-deficient state. Trials have shown that most patients in DKA will have mild to moderate elevations in serum lipid levels that improve with insulin therapy. (4) Two case series in adults showed that between 8% and 11% of patients in DKA developed severe HTG. (3)(5) There are several similar case reports of these findings in children, however, to our knowledge, this patient was the youngest reported case. (6)(7)(8)(9)(10)(11)(12)(13)Long-term HTG is associated with increased risk of cardiovascular disease. Acutely, the most significant consequence of severe HTG is acute pancreatitis. The risk of acute pancreatitis significantly increases with triglycerides greater than 973 mg/dL (11 mmol/L). (2) One study found that 36% of children with extreme HTG developed acute pancreatitis, whereas a larger of study of adults found 50% of patients with severe HTG in DKA developed acute pancreatitis. (1)(5) It is important to note that all patients in DKA are at an increased risk of acute pancreatitis, and that acute pancreatitis can also precipitate DKA by decreasing pancreatic reserve. Other complications of severe and extreme HTG include cutaneous eruptions, thrombosis, and inaccurate laboratory measurements. (2)(14)As in this case, laboratory inaccuracies secondary to the HTG may result in apparent difficulties correcting DKA. Although laboratories will clarify blood samples prior to analyzing results, lipemic specimens can artificially elevate serum glucose measurements, while artificially lowering sodium, chloride, and potassium values. (15)(16) Point of care glucometers in contrast may show pseudohypoglycemia. (17)Serum HTG can often be managed by removing the offending cause. Patients should be placed on a low-fat diet and, when appropriate, counseled to increase physical activity. Medications such as statins or fibrates may be considered for persistent severe HTG to reduce the risk of pancreatitis. (2) For severe or refractory cases, plasmapheresis has been used, and can reduce serum triglycerides by half. (18)For our patient case, pediatric endocrinology was consulted. Given the lack of a family history and the rapid improvement with insulin, it was thought that extreme HTG secondary to DKA was the most likely diagnosis. One month after discharge, serum lipids had entirely normalized, and genetic testing was not pursued.The authors thank the patient’s family for allowing them to share this case.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.219
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2020
Admission routes1
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