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Record W4404024054 · doi:10.1128/cmr.00087-24

American Society for Microbiology evidence-based laboratory medicine practice guidelines to reduce blood culture contamination rates: a systematic review and meta-analysis

2024· review· en· W4404024054 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.

Bibliographic record

VenueClinical Microbiology Reviews · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsQuest University Canada
FundersNational Cancer InstituteCenters for Disease Control and Prevention
KeywordsPhlebotomyMedicineBlood cultureVenipunctureSystematic reviewGuidelineMeta-analysisMEDLINEFalse positive paradoxBest practiceFamily medicineClinical microbiologyIntensive care medicinePathologySurgeryAntibioticsBiologyStatistics

Abstract

fetched live from OpenAlex

SUMMARYBlood cultures (BCs) are one of the critical tests used to detect bloodstream infections. BC results are not 100% specific. Interpretation of BC results is often complicated by detecting microbial contamination rather than true infection. False positives due to blood culture contamination (BCC) vary from 1% to as high as >10% of all BC results. False-positive BC results may result in patients undergoing unnecessary antimicrobial treatments, increased healthcare costs, and delay in detecting the true cause of infection or other non-infectious illness. Previous guidelines from the Clinical and Laboratory Standards Institute, College of American Pathologists, and others, based on expert opinion and surveys, promoted a limit of ≤3% as acceptable for BCC rates. However, the data supporting such recommendations are controversial. A previous systematic review of BCC examined three practices for reducing BCC rates (venipuncture, phlebotomy teams, and pre-packaged kits). Subsequently, numerous studies on different practices including using diversion devices, disinfectants, and education/training to lower BCC have been published. The goal of the current guideline is to identify beneficial intervention strategies to reduce BCC rates, including devices, practices, and education/training by providers in collaboration with the laboratory. We performed a systematic review of the literature between 2017 and 2022 using numerous databases. Of the 11,319 unique records identified, 311 articles were sought for full-text review, of which 177 were reviewed; 126 of the full-text articles were excluded based on pre-defined inclusion and exclusion criteria. Data were extracted from a total of 49 articles included in the final analysis. An evidenced-based committee's expert panel reviewed all the references as mentioned in Data Collection and determined if the articles met the inclusion criteria. Data from extractions were captured within an extraction template in the US Agency for Healthcare Research and Quality's Systematic Review Data Repository (https://srdr.ahrq.gov/). BCC rates were captured as the number of events (contaminated samples) per arm (standard practice versus improvement practice). Modified versions of the National Heart, Lung, and Blood Institute Study Quality Assessment Tools were used for risk of bias assessment (https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools). We used Grading of Recommendations, Assessment, Development and Evaluations to assess strength of evidence. There are several interventions that resulted in significant reduction in BCC rates: chlorhexidine as a disinfectant for skin preparation, using a diversion device prior to drawing BCs, using sterile technique practices, using a phlebotomy team to obtain BCs, and education/training programs. While there were no substantial differences between methods of decreasing BCC, our results indicate that the method of implementation can determine the success or failure of the intervention. Our evidence-based systematic review and meta-analysis support several interventions to effectively reduce BCC by approximately 40%-60%. However, devices alone without an education/training component and buy-in from key stakeholders to implement various interventions would not be as effective in reducing BCC rates.

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)0.013
metaresearch head score (Gemma)0.055
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.678
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.005
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.318
GPT teacher head0.527
Teacher spread0.209 · 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