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Record W4411967397 · doi:10.1016/j.cmi.2025.06.033

Empiric antibiotic therapy for moderate-to-severe community-acquired pneumonia: a systematic review and network meta-analysis

2025· review· en· W4411967397 on OpenAlexaff
Maryam Ghadimi, Reed Siemieniuk, Mark Loeb, João Pedro Lima, Danial Aminaei, Huda Gomaa, Ying Wang, Afeez Abiola Hazzan, John Basmaji, Liang Yao, William S.H. Kim, Alexandre Grant, Arnav Agarwal, Shahrzad Motaghi, Aran Tajika, T. Takayama, Giancarlo Alvarado‐Gamarra, Karin Kirmayr, Giovanna Eu Muti Schuenemann, Sara Zandieh, Aninditee Das, Veena Manja, Feryal Momenilandi, В. В. Лихванцев, Rachel Couban, Behnam Sadeghirad, Romina Brignardello-Petersen, Gordon Guyatt

Bibliographic record

VenueClinical Microbiology and Infection · 2025
Typereview
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsUniversity of AlbertaUniversity of CalgaryWestern UniversityImpactMcMaster University
FundersEinstein Stiftung Berlin
KeywordsMeta-analysisPneumoniaIntensive care medicineAntibiotic therapyMedicineAntibioticsCommunity-acquired pneumoniaSystematic reviewMEDLINEInternal medicineMicrobiologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The optimal empiric antibiotic regimen for moderate-to-severe community-acquired pneumonia (CAP) is uncertain. OBJECTIVES: To compare the effects of antibiotics for empiric therapy of moderate-to-severe CAP using a network meta-analysis. DATA SOURCES: Medline, EMBASE, Cochrane CENTRAL, Web of Science, and CINAHL from inception to 03 July 2024. STUDY ELIGIBILITY CRITERIA: Randomized controlled trials (RCT). PARTICIPANTS: Adults with moderate-to-severe CAP. 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: We conducted frequentist random-effect network meta-analyses addressing patient-important outcomes and assessed the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation approach. RESULTS: In total, 143 RCTs involving 29,157 participants proved eligible. Effects are in comparison with respiratory fluoroquinolones alone. Penicillins alone (relative risks [RR]: 1.25, 95% CI: 0.93-1.67; risk difference [RD]: 33 more per 1000, 95% CI: 9 fewer to 88 more), second-generation cephalosporins alone (RR: 1.34, 95% CI: 0.89-2.02; RD: 45 more per 1000, 95% CI: 15 fewer to 135 more), and third-generation cephalosporins alone (RR: 1.32, 95% CI: 0.99-1.77; RD: 42 more per 1000, 95% CI: 1 fewer to 102 more) or combined with a macrolide (RR: 1.34, 95% CI: 0.98-1.84; RD: 45 more per 1000, 95% CI: 3 fewer to 111 more) may be inferior in reducing treatment failure (all low certainty). The evidence among other antibiotic regimens for treatment failure and among all regimens for all-cause mortality, duration of hospitalization, and adverse events suggested little to no difference (in most cases with low certainty) or was very low certainty. CONCLUSIONS: For empiric treatment of moderate-to-severe CAP, none of the antibiotic regimens provided convincing evidence of important differences in any of the outcomes. TRIAL REGISTRATION NUMBER: PROSPERO (CRD42022297216).

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)0.007
metaresearch head score (Gemma)0.017
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.031
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.003
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 head0.189
GPT teacher head0.449
Teacher spread0.261 · 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
Published2025
Admission routes1
Has abstractno

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