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Effect of Detecting and Isolating <i>Clostridium difficile</i> Carriers at Hospital Admission on the Incidence of <i>C difficile</i> Infections

2016· article· en· W2343435145 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJAMA Internal Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcGill University Health CentreUniversité LavalCentre hospitalier universitaire de QuébecInstitut National de Santé Publique du QuébecInstitut Universitaire de Cardiologie et de Pneumologie de QuébecJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineClostridium difficileIncidence (geometry)C difficileClostridium InfectionsCross infectionIntensive care medicineEmergency medicineInternal medicineMicrobiologyAntibiotics

Abstract

fetched live from OpenAlex

IMPORTANCE: Clostridium difficile infection (CDI) is a major cause of health care-associated infection worldwide, and new preventive strategies are urgently needed. Current control measures do not target asymptomatic carriers, despite evidence that they can contaminate the hospital environment and health care workers' hands and potentially transmit C difficile to other patients. OBJECTIVE: To investigate the effect of detecting and isolating C difficile asymptomatic carriers at hospital admission on the incidence of health care-associated CDI (HA-CDI). DESIGN, SETTING, AND PARTICIPANTS: We performed a controlled quasi-experimental study between November 19, 2013, and March 7, 2015, in a Canadian acute care facility. Admission screening was conducted by detecting the tcdB gene by polymerase chain reaction on a rectal swab. Carriers were placed under contact isolation precautions during their hospitalization. MAIN OUTCOMES AND MEASURES: Changes in HA-CDI incidence level and trend during the intervention period (17 periods of 4 weeks each) were compared with the preintervention control period (120 periods of 4 weeks each) by segmented regression analysis and autoregressive integrated moving average (ARIMA) modeling. Concomitant changes in the aggregated HA-CDI incidence at other institutions in Québec City, Québec (n = 6) and the province of Québec (n = 94) were also examined. RESULTS: Overall, 7599 of 8218 (92.5%) eligible patients were screened, among whom 368 (4.8%) were identified as C difficile carriers. During the intervention, 38 patients (3.0 per 10 000 patient-days) developed an HA-CDI compared with 416 patients (6.9 per 10 000 patient-days) during the preintervention control period (P < .001). There was no immediate change in the level of HA-CDIs on implementation (P = .92), but there was a significant decrease in trend over time of 7% per 4-week period (rate ratio, 0.93; 95% CI, 0.87-0.99 per period; P = .02). ARIMA modeling also detected a significant effect of the intervention, represented by a gradual progressive decrease in the HA-CDI time series by an overall magnitude of 7.2 HA-CDIs per 10 000 patient-days. We estimated that the intervention had prevented 63 of the 101 (62.4%) expected cases. By contrast, no significant decrease in HA-CDI rates occurred in the control groups. CONCLUSIONS AND RELEVANCE: Detecting and isolating C difficile carriers was associated with a significant decrease in the incidence of HA-CDI. If confirmed in subsequent studies, this strategy could help prevent HA-CDI.

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.

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)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.010
GPT teacher head0.283
Teacher spread0.273 · 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