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Record W2106730538 · doi:10.1093/cid/cis340

Renal Failure and Leukocytosis Are Predictors of a Complicated Course of Clostridium difficile Infection if Measured on Day of Diagnosis

2012· article· en· W2106730538 on OpenAlexaff
Martijn P. Bauer, M.P.M. Hensgens, Mark A. Miller, Dale N. Gerding, Mark H. Wilcox, Adam P. Dale, Warren N. Fawley, Ed J. Kuijper, Sherwood L. Gorbach

Bibliographic record

VenueClinical Infectious Diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcGill UniversityJewish General Hospital
FundersSanofi PasteurAstellas PharmaGojo IndustriesPfizerViropharmaSanofiNabriva TherapeuticsMedicines Company
KeywordsLeukocytosisMedicineClostridium difficileInternal medicineConfidence intervalCreatinineRelative riskGastroenterologyIntensive care medicineAntibiotics

Abstract

fetched live from OpenAlex

Nonsevere Clostridium difficile infection (CDI) and severe CDI, which carries a higher risk than nonsevere CDI for treatment failure and CDI recurrence, are difficult to distinguish at the time of diagnosis. To investigate the prognostic value of 3 markers of severe CDI suggested by recent guidelines (fever, leukocytosis, and renal failure), we used the database of 2 randomized controlled trials, which contained information for 1105 patients with CDI. Leukocytosis (risk ratio [RR], 2.29; 95% confidence interval [CI], 1.63-3.21) and renal failure (RR, 2.52; 95% CI, 1.82-3.50) were associated with treatment failure. Fever, although associated with treatment failure (RR, 2.45; 95% CI, 1.07-5.61), was rare. Renal failure was the only significant predictor of recurrence (RR, 1.45; 95% CI, 1.05-2.02). Different timing of measurements of leukocyte count and serum creatinine level around the CDI diagnosis led to a different severity classification in many cases. In conclusion, both leukocytosis and renal failure are useful predictors, although timing of measurement is important.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.355
Teacher spread0.301 · 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

Citations86
Published2012
Admission routes1
Has abstractyes

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