Evidence map›Paper›PMID 39907452›Full record

ArticleMicrobiology spectrum2025

Antibiotic susceptibility of pathogens isolated in respiratory tract samples of recently hospitalized patients.

Anat Reiner-Benaim, Oryan Henig, Pilar Coronel, Mercedes Gimeno, Gilad Rozenberg, Dima Shlon, Ami Neuberger

Abstract read
In one paragraph

Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Anat Reiner-BenaimDepartment of Epidemiology, Biostatistics and Community Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Oryan HenigInfection Prevention and Control Unit, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Pilar CoronelScientific Department, Meiji Pharma Spain, Madrid, Spain.
Mercedes GimenoScientific Department, Meiji Pharma Spain, Madrid, Spain.
Gilad RozenbergUnit of Infectious Diseases, Rambam Healthcare Campus, Haifa, Israel.
Dima ShlonDepartment of Internal Medicine D, Division of Internal Medicine, Rambam Healthcare Campus, Haifa, Israel.ORCID 0009-0005-5015-6323
Ami NeubergerUnit of Infectious Diseases, Rambam Healthcare Campus, Haifa, Israel.ORCID 0009-0002-4113-5326

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Community-acquired lower respiratory tract infections (CA-LRTIs) treatment is largely empirical as microbiologic testing is rarely performed. Here, we provide microbiologic data of severe CA-LRTI cases requiring hospitalization. We aim to describe the distribution and susceptibility patterns of pathogens causing severe CA-LRTI. We analyzed respiratory samples from recently admitted patients with CA-LRTIs to assess pathogen distribution and antibiotic susceptibility patterns. We divided patients into three groups: CA-LRTI and no prior healthcare exposure, CA-LRTI with healthcare exposure, and patients diagnosed with LRTI 48 to 7 days of hospital admission. In a sub-cohort, we assessed the bacteria's susceptibility to cefditoren. A total of 1,395, 2,212, and 2,760 samples were included in the three study groups. Gram-negative bacteria were the most common bacteria isolated.

Indexed as

Anti-Bacterial AgentsBacteriaCommunity-Acquired InfectionsRespiratory SystemRespiratory Tract InfectionsAdultAgedAged, 80 and overDrug Resistance, BacterialFemaleHospitalizationHumansMaleMicrobial Sensitivity TestsMiddle AgedYoung AdultAnti-Bacterial Agentscommunity acquired infectionslower respiratory tract infectionmicrobiologypathogenspneumonia

Identifiers

PMID39907452
PMCPMC11878021

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.