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Record W4399160563 · doi:10.1016/j.cmi.2024.05.017

Empiric antibiotic regimens in adults with non-ventilator-associated hospital-acquired pneumonia: a systematic review and network meta-analysis of randomized controlled trials

2024· review· en· W4399160563 on OpenAlexaff
Maryam Ghadimi, Reed Siemieniuk, Mark Loeb, Afeez Abiola Hazzan, Danial Aminaei, Huda Gomaa, Ying Wang, Liang Yao, Arnav Agarwal, John Basmaji, Alexandre Grant, William S.H. Kim, Giancarlo Alvarado‐Gamarra, В. В. Лихванцев, João Pedro Lima, Shahrzad Motaghi, Rachel Couban, Behnam Sadeghirad, Romina Brignardello‐Petersen

Bibliographic record

VenueClinical Microbiology and Infection · 2024
Typereview
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsUniversity of CalgaryUniversity of AlbertaWestern UniversityMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineVentilator-associated pneumoniaPneumoniaIntensive care medicineMeta-analysisRegimenRandomized controlled trialAntibioticsHospital-acquired pneumoniaInternal medicineMicrobiologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The optimal empiric antibiotic regimen for non-ventilator-associated hospital-acquired pneumonia (HAP) is uncertain. OBJECTIVES: To compare the effectiveness and safety of alternative empiric antibiotic regimens in HAP using a network meta-analysis. DATA SOURCES: Medline, EMBASE, Cochrane CENTRAL, Web of Science, and CINAHL from database inception to July 06, 2023. STUDY ELIGIBILITY CRITERIA: RCTs. PARTICIPANTS: Adults with clinical suspicion of HAP. INTERVENTIONS: Any empiric antibiotic regimen vs. another, placebo, or no treatment. ASSESSMENT OF RISK OF BIAS: Paired reviewers independently assessed risk of bias using a modified Cochrane tool for assessing risk of bias in randomized trials. METHODS OF DATA SYNTHESIS: Paired reviewers independently extracted data on trial and patient characteristics, antibiotic regimens, and outcomes of interest. We conducted frequentist random-effects network meta-analyses for treatment failure and all-cause mortality and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development and Evaluation approach. RESULTS: Thirty-nine RCTs proved eligible. Thirty RCTs involving 4807 participants found low certainty evidence that piperacillin-tazobactam (RR compared to all cephalosporins: 0.65; 95% CI: 0.42, 1.01) and carbapenems (RR compared to all cephalosporins: 0.77; 95% CI: 0.53, 1.11) might be among the most effective in reducing treatment failure. The findings were robust to the secondary analysis comparing piperacillin-tazobactam vs. antipseudomonal cephalosporins or antipseudomonal carbapenems vs. antipseudomonal cephalosporins. Eleven RCTs involving 2531 participants found low certainty evidence that ceftazidime and linezolid combination may not be convincingly different from cephalosporin alone in reducing all-cause mortality. Evidence on other antibiotic regimens is very uncertain. Data on other patient-important outcomes including adverse events was sparse, and we did not perform network or pairwise meta-analysis. CONCLUSIONS: For empiric antibiotic therapy of adults with HAP, piperacillin-tazobactam might be among the most effective in reducing treatment failure. Empiric methicillin-resistant Staphylococcus aureus coverage may not exert additional benefit in reducing mortality. REGISTRATION: PROSPERO (CRD 42022297224).

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)0.036
metaresearch head score (Gemma)0.092
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.036
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.092
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.036
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
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 head0.083
GPT teacher head0.420
Teacher spread0.337 · 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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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