Predictive Factors of Clostridium difficile Infection in Hospital Inpatients
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".