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Record W2017601550 · doi:10.4021//jmc.v3i6.799

A Rare Complication of Antibiotic (Piperacillin/Tazobactam) Therapy: Resistant Hypokalemia

2012· article· en· W2017601550 on OpenAlexvenueno aff
Faruk Kutlutürk, Süheyla Uzun Kaya, Türker Taşlıyurt, Şafak Şahin, Şener Barut, Banu Öztürk, Abdülkerim Yılmaz

Bibliographic record

VenueJournal of Medical Cases · 2012
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsHypokalemiaMedicinePiperacillin/tazobactamTazobactamPiperacillinAntibioticsBeta-Lactamase InhibitorsIntensive care medicineComplicationInternal medicineMicrobiologyAntibiotic resistanceBacteria

Abstract

fetched live from OpenAlex

Piperacillin/tazobactam is a commonly used antibiotic with tolerable side effects and broad antimicrobial activity in general practice. Here in we report a patient with resistant and severe hypokalemia induced by piperacillin/tazobactam. There were no other underlying renal or hepatic illness and other causes of hypokalemia. When the treatment was stopped, hypokalemia resolved immediately without potassium replacement. We also evaluated the causality of the case report. We concluded this causality as probable/likely category according to WHO-UMC Causality Categories. We concluded that piperacillin/tazobactam may be cause severe hypokalemia and we must be careful to monitor of serum electrolytes especially potassium during antibiotic treatment. doi: http://dx.doi.org/10.4021/jmc799w

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)0.004
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.182
GPT teacher head0.467
Teacher spread0.285 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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