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Record W1647944961 · doi:10.1016/j.bjid.2015.05.005

Application of the ATLAS score for evaluating the severity of Clostridium difficile infection in teaching hospitals in Mexico

2015· article· en· W1647944961 on OpenAlexaff
Raúl Hernández-García, Elvira Garza‐González, Mark A. Miller, Giovanna Yazmin Arteaga Muller, Alejandra M. Galván-De los Santos, Adrián Camacho-Ortíz

Bibliographic record

VenueThe Brazilian Journal of Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineClostridium difficileInternal medicineObservational studyAntibioticsIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: For clinicians, a practical bedside tool for severity assessment and prognosis of patients with Clostridium difficile infection is a highly desirable unmet medical need. SETTING: Two general teaching hospitals in northeast Mexico. POPULATION: Adult patients with C. difficile infection. METHODS: Prospective observational study. RESULTS: Patients included had a median of 48 years of age, 54% of male gender and an average of 24.3 days length of hospital stay. Third generation cephalosporins were the antibiotics most commonly used prior to C. difficile infection diagnosis. Patients diagnosed with C. difficile infection had a median ATLAS score of 4 and 56.7% of the subjects had a score between 4 and 7 points. Patients with a score of 8 through 10 points had 100% mortality. CONCLUSION: The ATLAS score is a potentially useful tool for the routine evaluation of patients at the time of C. difficile infection diagnosis. At 30 days post-diagnosis, patients with a score of ≤3 points had 100% survival while all of those with scores ≥8 died. Patients with scores between 4 and 7 points had a greater probability of colectomy with an overall cure rate of 70.1%.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.098
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.343
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.

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

Citations27
Published2015
Admission routes1
Has abstractyes

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