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Record W4317567726 · doi:10.2147/idr.s397513

Bacterial Epidemiology and Antimicrobial Resistance Profiles of Respiratory Specimens of Children with Pneumonia in Hainan, China

2023· article· en· W4317567726 on OpenAlex
Wenhui Mai, Yiwei Liu, Qiaoyi Meng, Jianping Xu, Jinyan Wu

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

VenueInfection and Drug Resistance · 2023
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsMcMaster University
FundersNatural Science Foundation of Hainan ProvinceNational Natural Science Foundation of China
KeywordsMoraxella catarrhalisMicrobiologyStreptococcus pneumoniaeHaemophilus influenzaeAntibiotic resistanceBiologyAcinetobacter baumanniiPneumoniaPseudomonas aeruginosaAntimicrobialSputumKlebsiella pneumoniaeKlebsiella pneumoniaAcinetobacterAntibioticsMedicineBacteriaEscherichia coliInternal medicineTuberculosis

Abstract

fetched live from OpenAlex

Purpose: To investigate the bacterial species and antimicrobial susceptibility of respiratory specimens of children with pneumonia in Hainan, China. Methods: A total of 5017 specimens, including 4986 sputum samples, 19 bronchoalveolar lavage fluid samples and 12 tracheal tube tip samples from hospitalized children with pneumonia from April 1, 2021 to March 31, 2022 were studied. All the bacterial isolates were identified and confirmed with the VITEK 2 system. Antimicrobial susceptibility of all isolates was determined using the Kirby-Bauer method or the VITEK 2 Compact automatic system, following the breakpoints recommended by the Clinical and Laboratory Standards Institute. Results: A total of 996 bacterial isolates were collected and classified into 24 species. The top 10 most frequent species were Haemophilus influenzae (356 isolates, 35.7%), Streptococcus pneumoniae (128, 12.9%), Moraxella catarrhalis (114, 11.5%), Escherichia coli (89, 8.9%), Staphylococcus aureus (89, 8.9%), Klebsiella pneumoniae (82, 8.2%), Acinetobacter baumannii (31, 3.1%), Pseudomonas aeruginosa (28, 2.8%), Enterobacter cloacae (18, 1.8%), and Streptococcus agalactiae (13, 1.3%). 70.5% strains had the resistant (R) and/or intermediate (I) phenotypes to at least one of the tested drugs, with a large proportion (54.6%) showing resistance to two or more commonly used antibiotics. In addition, 60.5% (69/114) of M. catarrhalis strains and 42.9% (153/356) of H. influenzae strains produced β-lactamases while 19.1% (17/89) E. coli and 6.1% (5/82) K. pneumoniae strains produced extended-spectrum β-lactamases. Conclusion: A diversity of pathogenic bacteria were isolated from the respiratory tract of children with pneumonia in Hainan, China. High-frequency resistance to first-line antimicrobial drugs was observed in Gram-negative and Gram-positive bacteria, including 544 isolates resistant to at least two antibiotics. Rapid identification and susceptibility testing should be implemented for children with bacterial pneumonia in Hainan before drug treatment is recommended. Keywords: pneumonia, bacteria, antimicrobial resistance, children, multidrug-resistant bacteria

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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