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Record W2899250743 · doi:10.14740/wjnu366

Unusual Case of Foreign Body Esophagus Presenting With Acute Kidney Injury: Case Report and Literature Review

2018· article· en· W2899250743 on OpenAlexvenueno aff
Sudha Shahi, Tika Ram Bhandari, Tridip Pantha

Bibliographic record

VenueWorld Journal of Nephrology and Urology · 2018
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEsophagusMediastinitisForeign bodyImpactionComplicationSurgerySepsisForeign BodiesAcute kidney injuryGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Foreign bodies in esophagus are more common in children, elderly and psychiatry patients. Different types of foreign bodies can get impacted in esophagus, such as coins, bone pieces and meat bolus. Approximately 80% of foreign bodies are said to pass spontaneously without any intervention. Emergent endoscopic retrieval or rigid esophagoscopy are the treatment of choice. Delayed diagnosis can lead to respiratory failure, sepsis or hemorrhage. Nevertheless, esophageal foreign bodies are no more matter of serious concerns to the surgeons in terms of early diagnosis and management given the advancement in the diagnostic tools. Eventually delayed management and complications due to prolonged foreign body impaction are less in the picture nowadays. Here we present a typical case of foreign body esophagus that presented with acute kidney injury which was delayed to reach help due to various factors, such as poor economic background of the patient, poor access to health service and prevalence of social beliefs. Cases of complications like respiratory failure, sepsis, mediastinitis and hemorrhage have been reported very frequently, but cases presenting with acute kidney injury seem to be reported very less in literature. Thus, we believe that this case will add acute kidney injury to another possible complication of delayed foreign body esophagus. World J Nephrol Urol. 2018;7(3-4):78-81 doi: https://doi.org/10.14740/wjnu366

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.301
Teacher spread0.291 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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