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Record W4390394958 · doi:10.37811/cl_rcm.v7i6.8900

Clostridioides Difficile: Infección, Diagnóstico y Tratamientos Prometedores. Revisión Bibliográfica

2023· article· es· W4390394958 on OpenAlexaff
Nubia Guzmán Rodríguez, Mabel Guzmán

Bibliographic record

VenueCiencia Latina Revista Científica Multidisciplinar · 2023
Typearticle
Languagees
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineFecal bacteriotherapyHumanitiesClostridium difficileMicrobiologyAntibioticsPhilosophyBiology

Abstract

fetched live from OpenAlex

Clostridioides difficile (CD), la bacteria responsable de infecciones intestinales que se manifiestan tras el uso de antibióticos, puede desencadenar desde síntomas leves hasta colitis pseudomembranosa. El diagnóstico implica pruebas de heces y, en casos graves, colonoscopias. Aunque el tratamiento inicial incluye antibióticos, el trasplante fecal, restaurador de la microbiota intestinal, ha demostrado una efectividad superior al 90% en infecciones recurrentes. A pesar de los desafíos y cuestionamientos, su uso cuenta con el respaldo de la FDA. Por otro lado, otras investigaciones están explorando el uso de aislados bacterianos y esporas como alternativas para la prevención y tratamiento de la infección para mitigar los posibles efectos secundarios que conlleva el uso de los trasplantes fecales. Además, aunque su eficacia no está claramente establecida, en ciertos casos el empleo de probióticos también es considerado como una medida preventiva durante el uso de antibióticos. A pesar de los avances en las estrategias de tratamiento para esta infección, la prevención sigue siendo fundamental, y se logra mediante precauciones en el uso de antibióticos y prácticas de higiene que permitan controlar estas infecciones.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.038
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.008

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 head0.037
GPT teacher head0.334
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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