MétaCan
Menu
Back to cohort
Record W2114855632 · doi:10.1186/1710-1492-10-52

Allopurinol desensitization with A 2 weeks modified protocol in an elderly patients with multiple comorbidities: a case report

2014· article· en· W2114855632 on OpenAlexvenueno aff
Adile Berna Dursun, Osman Zikrullah Şahin

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2014
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsAllopurinolMedicineGoutDesensitization (medicine)FurosemideInternal medicineDiscontinuationRashGastroenterologyUrologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Allopurinol is an effective urate-lowering drug that is well tolerated by the majority of patients. Patients with chronic renal insufficiency have an increased risk of hypersensitivity reactions with allopurinol. CASE PRESENTATION: 75 year old male patient with gout, renal insufficiency, history of metastatic colorectal carcinoma status post-resection was referred to Allergy clinic for a maculopapular eruption that developed 1 week after initiating therapy with allopurinol. The rash resolved with discontinuation of allopurinol. However, his serum urate level rose to 19.9 mg/dl. We initially proposed a slow 4 week oral allopurinol desensitization. The treating nephrologist felt it was critical to lower urate more rapidly. As a result, we modified the dose and standard 4 week protocol down to 2 weeks. A suspension of allopurinol was prepared by the allergy nurse practitioner with a 300 mg allopurinol tablet. The sensitization protocol was modified as a starting dose of 0.3 mg escalating to a final dose of 300 mg/day in 2 weeks. There was no reaction during or after the desensitization. The patient's urate level normalized (6.3 mg/dl) and has continued on 300 mg allopurinol daily without reaction. CONCLUSION: A 2 week modified allopurinol desensitization protocol is a safe alternative for elderly patients with multiple comorbidities.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.629

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 head0.023
GPT teacher head0.317
Teacher spread0.294 · 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".

Quick stats

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAllergy Asthma and Clinical ImmunologySame topicDrug-Induced Adverse ReactionsFrench-language works237,207