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Record W2757468034 · doi:10.1093/ofid/ofx163.953

Tetracyclines are Associated with a Reduced Risk of Clostridium difficile Infection: A Systematic Review and Meta-analysis

2017· review· en· W2757468034 on OpenAlexaboutno aff
Raseen Tariq, Janice Cho, Saloni Kapoor, Robert Orenstein, Siddharth Singh, Darrell S. Pardi, Sahil Khanna

Bibliographic record

VenueOpen Forum Infectious Diseases · 2017
Typereview
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineClostridium difficileMeta-analysisAntibioticsInternal medicineAntimicrobial stewardshipMEDLINECohort studyDoxycyclineSubgroup analysisAntibiotic resistanceMicrobiology

Abstract

fetched live from OpenAlex

Abstract Background Efforts towards antibiotic stewardship help reduce risk of Clostridium difficile infection (CDI) but there is a need to delineate antibiotic choices to reduce CDI risk. Tetracyclines may be associated with a low risk for CDI but the evidence is conflicting. We conducted a systematic review and meta-analysis to determine the relationship between tetracyclines use and CDI. Methods A systematic search of Medline, Embase, and Web of Science was performed from January 1978 up to December 2016 including studies assessing the association between tetracyclines and CDI; compared with other antibiotics; to assess the risk of CDI after exposure to tetracyclines vs. other antibiotics. Study quality was assessed using the Newcastle-Ottawa scale. Weighted summary estimates were calculated using generalized inverse variance with random-effects model using Review Manager version 5.3 (Cochran Inc). Results Six studies; 4 case control and 2 cohort studies reported the association of CDI with tetracyclines or other antibiotics prior to CDI including patients from 1993 to 2012. Meta-analysis of all studies using the random-effects model demonstrated that tetracyclines were associated with decreased risk of CDI compared with other antibiotics (OR, 0.62; 95% CI, 0.47–0.81; P = .0005). There was significant heterogeneity among the studies, with an I2 of 53% (Figure 1). No publication bias was seen. Subgroup analysis of studies evaluating the risk of CDI with doxycycline only also demonstrated a decreased risk of CDI with doxycycline compared with other antibiotics (OR, 0.55; 95% CI, 0.40–0.75; P = 0.0002). A subgroup analysis based on CDI diagnosis definitions revealed a decreased risk of CDI with tetracyclines (OR, 0.59; 95% CI, 0.44–0.80; P = 0. 0006) in studies that used clinical definitions (presence of diarrhea with a positive stool test), but not among the studies that used ICD-9 codes for CDI diagnosis (OR, 0.95; 95% CI, 0.45–2.01; P = 0.90). Conclusion Tetracyclines are associated with a lower risk of developing CDI compared with other antibiotics. It is reasonable to use these over other antibiotics when appropriate (community acquired pneumonia, bronchitis, chlamydia, rickettsial or spirochetal infections) to reduce the risk of CDI. Forest plot demonstrating decreased odds of CDI with tetracyclines use by a random-effects model 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.035
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.039
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.110
GPT teacher head0.400
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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