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Evaluation of the Association Between Gastric Acid Suppression and Risk of Intestinal Colonization With Multidrug-Resistant Microorganisms

2020· review· en· W3006822124 on OpenAlexaboutno aff
Roel P J Willems, Karin van Dijk, Johannes C. F. Ket, Christina M. J. E. Vandenbroucke‐Grauls

Bibliographic record

VenueJAMA Internal Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColonizationMultiple drug resistanceMicroorganismMicrobiologyInternal medicineGastroenterologyAntibioticsBacteriaGenetics

Abstract

fetched live from OpenAlex

Importance: Acid suppressants inhibit gastric acid secretion and disrupt the intestinal microbiome. Whether acid suppression increases the risk of colonization with multidrug-resistant microorganisms (MDROs) is unclear. Objectives: To systematically examine the association of use of acid suppressants with the risk of colonization with MDROs and to perform a meta-analysis of current evidence. Data Sources: PubMed, Embase, the Web of Science Core Collection, and the Cochrane Central Register of Controlled Trials were searched from database inception through July 8, 2019. Study Selection: Study selection was performed independently by 2 authors (R.P.J.W. and C.M.J.E.V.-G.) on the basis of predefined selection criteria; conflicts were resolved by consensus or by an adjudicator (K.v.D.). Human observational studies (case control, cohort, and cross-sectional) and clinical trial designs were selected if they quantified the risk of MDRO colonization in users of acid suppressants in comparison with nonusers. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations were followed. Data were extracted independently by the same 2 authors, and adjudication was conducted when necessary. Risk of bias was assessed according to a modified Newcastle-Ottawa Scale. Pooled odds ratios (ORs) were estimated using random-effects models; heterogeneity was evaluated using the I2 method. Main Outcomes and Measures: The primary outcome measure was intestinal colonization with MDROs of the Enterobacterales order (producing extended-spectrum β-lactamases, carbapenemases, or plasmid-mediated AmpC β-lactamases), vancomycin-resistant enterococci, methicillin-resistant or vancomycin-resistant Staphylococcus aureus, or multidrug-resistant Pseudomonas or Acinetobacter species. Results: A total of 26 observational studies including 29 382 patients (11 439 [38.9%] acid suppressant users) met the selection criteria. Primary meta-analysis of 12 studies including 22 305 patients that provided adjusted ORs showed that acid suppression increased the odds of intestinal carriage of MDROs of the Enterobacterales order and of vancomycin-resistant enterococci by roughly 75% (OR = 1.74; 95% CI, 1.40-2.16; I2 = 68%). The odds were concordant with the secondary pooled analysis of all 26 studies (OR = 1.70; 95% CI, 1.44-1.99; I2 = 54%). Heterogeneity was partially explained by variations in study setting and the type of acid suppression. Conclusions and Relevance: Acid suppression is associated with increased odds of MDRO colonization. Notwithstanding the limitations of observational studies, the association is plausible and is strengthened by controlling for confounders. In view of the global increase in antimicrobial resistance, stewardship to reduce unnecessary use of acid suppressants may help to prevent MDRO colonization.

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)0.034
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.077
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.027
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.342
Teacher spread0.305 · 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 designSystematic review
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".

Quick stats

Citations95
Published2020
Admission routes1
Has abstractyes

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