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Record W2567598819 · doi:10.1093/ofid/ofw172.1648

Predictive Factors of Clostridium difficile Infection in Hospital Inpatients

2016· article· en· W2567598819 on OpenAlexaffabout
Koray Demir, Matthew P. Cheng, Todd C. Lee

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineClostridium difficileC difficileInternal medicineClostridium InfectionsMicrobiologyIntensive care medicineAntibiotics

Abstract

fetched live from OpenAlex

Background. Diagnostic testing for Clostridium difficile infection (CDI) has been revolutionized by the advent of a highly sensitive polymerase chain reaction assay; however, it is unable to distinguish between colonization and infection. Consequently, a positive result in the setting of a low pre test probability may represent a false-positive. Since diarrhea is common in hospitalized patients, this could have major implications for testing and treatment. The objective of our study was to identify clinical and laboratory findings that correlated with patients who had positive test results and were treated for CDI, in order to answer: “does this medical inpatient with diarrhea have C. difficile infection?” Table: Factors Independently Associated With CDI in Tested Patients Abbreviations: CDI = Clostridium difficile infection; WBC = white blood cell. Methods. We conducted a retrospective cohort study on the medical Clinical Teaching Units (CTU) of the Royal Victoria Hospital (Montréal, Canada). Patients were included if they had a C. difficile polymerase chain reaction on the CTU between January 2014 and September 2015 and their admission diagnosis was not C. difficile. CDI was defined as a patient with a positive toxin assay who received a full course of treatment. Clinical and laboratory data were extracted from hospital records. Independent predictors of CDI were determined by logistic regression. Results. Data were available on 319 patients, of whom 274 tested negative (86%). Of the 45 patients who tested positive, 43 (95.6%) received treatment. A number of factors were independently associated with CDI, as shown in the table. The area under the receiver-operator curve (c-statistic) for the model was 0.78. An active laxative prescription was unhelpful in ruling out CDI. Conclusion. Various clinical factors in our cohort seem promising to differentiate between those medical inpatients with CDI and other causes of diarrhea. A preliminary clinical prediction rule derived from this data (http://goo.gl/xgDao9) will need to be further refined and validated in a larger cohort. Disclosures. All authors: No reported disclosures.

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)0.001
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 score0.010
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.012
GPT teacher head0.303
Teacher spread0.290 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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