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Record W4411773878 · doi:10.48048/tis.2025.9681

Comparative Effectiveness of Single, Dual, and Multi-Antibiotic Therapies in Managing Carbapenem-Resistant Enterobacterales: A Systematic Review and Meta-Analysis on Survival Rates

2025· review· en· W4411773878 on OpenAlexaboutno aff
Enny Suswati, Muhammad Farhan Hibatulloh, Dhiani Eka Putri

Bibliographic record

VenueTrends in Sciences · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersUniversitas Jember
KeywordsMeta-analysisCarbapenemMedicineAntibioticsInternal medicineMicrobiologyBiology

Abstract

fetched live from OpenAlex

Carbapenem-resistant Enterobacterales (CRE) represent a major global health issue, linked to elevated rates of morbidity and mortality stemming from restricted treatment alternatives. The Gram-negative bacteria, such as Klebsiella pneumoniae and Escherichia coli, are significant contributors to severe infections, including bacteremia, pneumonia, and urinary tract infections. Mechanisms of resistance such as the production of carbapenemases, the action of efflux pumps, and mutations in porins diminish the effectiveness of carbapenems, which are frequently the antibiotics of last resort. In light of this escalating concern, the absence of a universally recognized global guideline for the management of CRE results in diverse treatment strategies. This systematic review and meta-analysis aimed to evaluate the effectiveness of monotherapy, dual therapy, and multi-antibiotic regimens in the treatment of CRE infections. In accordance with established guidelines, data from 5 major databases were analyzed, and the quality of the studies was evaluated using the Newcastle-Ottawa Scale. The findings indicated that combination therapy led to a notable enhancement in survival rates when contrasted with monotherapy (OR = 0.69, 95 % CI 0.62 - 0.78, p < 0.00001). In contrast, no significant difference was found between dual therapy and multi-antibiotic regimens (OR = 1.17, 95 % CI 0.95 - 1.46, p = 0.15). The combination therapy exhibited synergistic effects, improving bacterial eradication while reducing the emergence of resistance. Dual therapy demonstrated superior outcomes when contrasted with multi-antibiotic regimens, presenting lower toxicity risks and enhanced patient adherence. Nonetheless, the absence of stratification considering resistance mechanisms, infection severity, and patient characteristics highlights the necessity for tailored treatment strategies. In conclusion, this study emphasizes the critical necessity for internationally standardized protocols for CRE management to guarantee uniform and effective treatment. Future investigations should concentrate on resistance profiling, assessing the safety and cost-effectiveness of dual and multi-antibiotic regimens, and customizing therapies to individual patient factors to enhance outcomes. HIGHLIGHTS This article presents a systematic review and meta-analysis on the effectiveness of antibiotic strategies in managing carbapenem-resistant Enterobacterales (CRE) infections. Combination antibiotic therapy significantly improves patient survival rates compared to monotherapy in CRE infections. No statistically significant difference in survival was observed between dual-antibiotic and multi-antibiotic regimens, though dual therapy demonstrated clinical advantages. This review suggests that Dual therapy offers reduced toxicity risk and improved patient adherence, making it a safer and more feasible option than multiple-antibiotic regimens. The study emphasizes the need for globally standardized CRE treatment protocols and future research that incorporates resistance profiles and patient-specific factors. GRAPHICAL ABSTRACT

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)0.025
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 score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.025
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.045
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
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 head0.114
GPT teacher head0.406
Teacher spread0.292 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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