Unusual Case of Foreign Body Esophagus Presenting With Acute Kidney Injury: Case Report and Literature Review
Bibliographic record
Abstract
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
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".