Impact of the Type of Diagnostic Assay on Clostridium difficile Infection and Complication Rates in a Mandatory Reporting Program
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Most Clostridium difficile infection (CDI) surveillance programs neither specify the diagnostic method to be used nor stratify rates accordingly. We assessed the difference in healthcare-associated CDI (HA-CDI) incidence and complication rates obtained by 2 validated diagnostic methods. METHODS: This was a prospective cohort study of patients for whom a C. difficile test was ordered between 1 August 2010 and 31 July 2011. All specimens were tested in parallel by a commercial polymerase chain reaction (PCR) assay targeting toxin B gene tcdB, and a 3-step algorithm detecting glutamate dehydrogenase and toxins A and B by enzyme immunoassay and cell culture cytotoxicity assay (EIA/CCA). CDI incidence rate ratios were calculated using univariate Poisson regression. RESULTS: A total of 1321 stool samples were tested during a period totaling 95 750 patient-days. Eighty-five HA-CDI cases were detected by PCR and 56 cases by EIA/CCA (P = .01). The overall incidence rate was 8.9 per 10 000 patient-days (95% confidence interval [CI], 7.1-10.9) by PCR and 5.8 per 10 000 patient-days (95% CI, 4.4-7.4) by EIA/CCA (P = .01). The incidence rate ratio comparing PCR and EIA/CCA was 1.52 (95% CI, 1.08-2.13; P = .015). Overall complication rate was 27% (23/85) when CDI was diagnosed by PCR and 39% (22/56) by EIA/CCA (P = .16). Cases detected by PCR only were less likely to develop a complication of CDI compared with cases detected by both PCR and EIA/CCA (3% vs 39%, respectively; P < .001). CONCLUSIONS: Performing PCR instead of EIA/CCA is associated with a >50% increase in the CDI incidence rate. Standardization of diagnostic methods may be indicated to improve interhospital comparison.
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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 | 0.001 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it