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Record W3125641072 · doi:10.1159/000509952

Recurrent Encephalopathy and Severe Anion Gap Metabolic Acidosis in a Patient with Short Bowel: It Is D-Lactic Acidosis

2021· article· en· W3125641072 on OpenAlexaff
Avni Jain, Kiran Jhinger, Jonathon Bellas

Bibliographic record

VenueCase Reports in Gastroenterology · 2021
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLactic acidosisMedicineEtiologyEncephalopathyShort bowel syndromeMetabolic acidosisAnion gapAcidosisInternal medicineGastroenterologyAtaxiaPediatricsParenteral nutrition

Abstract

fetched live from OpenAlex

D-lactic acidosis is a rare and potentially underrecognized condition in patients with short bowel syndrome. We present the case of a 61-year-old female with a history of an ileojejunal bypass at age 18 who presented to hospital with acute-onset encephalopathy, ataxia, and severe anion gap metabolic acidosis (AGMA). On initial investigations there were no identifiable etiologies for the AGMA. Further history revealed that she had been experiencing these symptoms on a recurrent basis for the past 40 years. An oral carbohydrate load was given to the patient in hospital which reproduced her symptoms and the AGMA. A serum D-lactate level returned elevated several weeks later. A 2-month follow-up revealed that all her symptoms had ceased with limitation of carbohydrates to 150 g per day. Patients with short bowel syndrome are susceptible to developing D-lactic acidosis due to the large carbohydrate loads that are delivered to the colon, where they are then metabolized. Due to its rarity, it is likely that there is a delay in recognition of this condition. This case report describes a common clinical presentation of this rare condition and describes the pathophysiology, diagnosis, and management of D-lactic acidosis in small bowel syndrome.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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".

Quick stats

Citations7
Published2021
Admission routes1
Has abstractyes

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