MétaCan
Menu
Back to cohort

Indications of a new antibiotic in clinical practice: results of the tigecycline initial use registry

2008· article· en· W2167520815 on OpenAlexaff
Daniel Curcio, F. FERNÁNDEZ, Alejandro Cané, Laura Barcelona, Daniel Stamboulián

Bibliographic record

VenueThe Brazilian Journal of Infectious Diseases · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsTigecyclineMedicineColistinIntensive care medicineAntibioticsAcinetobacterMedical prescriptionPneumoniaMultiple drug resistanceInternal medicinePharmacologyMicrobiology

Abstract

fetched live from OpenAlex

Tigecycline is the first of a new class of antibiotics named glycylcyclines and it was approved for the treatment of complicated intra-abdominal infections and complicated skin and skin structure infections. Notwithstanding this, tigecycline's pharmacological and microbiological profile which includes multidrug-resistant pathogens encourages physicians' use of the drug in other infections. We analyzed, during the first months after its launch, the tigecycline prescriptions for 113 patients in 12 institutions. Twenty-five patients (22%) received tigecycline for approved indications, and 88 (78%) for "off label" indications (56% with scientific support and 22% with limited or without any scientific support). The most frequent "off label" use was ventilator associated pneumonia (VAP) (63 patients). The etiology of infections was established in 105 patients (93%). MDR-Acinetobacter spp. was the microorganism most frequently isolated (50% of the cases). Overall, attending physicians reported clinical success in 86 of the 113 patients (76%). Our study shows that the "off label" use of tigecycline is frequent, especially in VAP. due to MDR-Acinetobacter spp., where the therapeutic options are limited (eg: colistin). Physicians must evaluate the benefits/risks of using this antibiotic for indications that lack rigorous scientific support.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.334
Teacher spread0.312 · 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.

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

Citations31
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThe Brazilian Journal of Infectious DiseasesSame topicAntibiotic Resistance in BacteriaFrench-language works237,207