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Record W4237229918 · doi:10.21203/rs.3.rs-31964/v1

Detection and Characterization of Carbapenem resistant Gram-negative bacilli isolates recovered from hospitalized patients at Soba University Hospital, Sudan

2020· preprint· en· W4237229918 on OpenAlexaff
Hana S. Elbadawi, Kamal M. Elhag, El Sheikh Mahgoub, Hisham N. Altayb, Francine Ntoumi, Linzy Elton, Timothy D. McHugh, Mohamed Osman, John Tembo, Giuseppe Ippolito, Alimuddin Zumla, Muzamil Mahdi Abdel Hamid

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsYork University
FundersEuropean and Developing Countries Clinical Trials PartnershipNational Institutes of HealthMinistero della Salute
KeywordsGramBacilliMicrobiologyCarbapenemMedicineGram-negative bacterial infectionsGram-negative bacteriaBiologyBacteriaAntibiotics

Abstract

fetched live from OpenAlex

Abstract Background:Antimicrobial resistance (AMR) poses a threat to global health security. Whilst over the past decade, there has been an increase in reports of nosocomial infections globally caused by carbapenem resistant Gram-negative bacilli (GNB), data from Africa have been scanty. We performed a study of carbapenem resistance genes among GNB isolated from patients treated in hospitals in Khartoum state, Sudan.Methods:A cross-sectional study was conducted at Soba University Hospital (SUH) and Institute of Endemic Diseases, University of Khartoum for the period October 2016 to February 2017. A total of 206 GNB isolates from different clinical specimens were analyzed for carbapenem resistance genes using phenotypic tests and affirmed by genes detection. Multiplex PCR was performed for each strain to detect the carbapenemase genes, including the blaNDM, blaVIM, blaIMP, blaKPC, and blaOXA-48. In addition to blaCTXM, blaTEM and blaSHV. DNA sequencing and bioinformatics analysis were used to detect genes subtypes.Findings:Of 206 isolates, 171 (83%) were confirmed resistant phenotypically and 121 (58.7%) isolates were positive for the presence of one or more carbapenemase gene. New Delhi metallo-β-lactamase (NDM) types were the most predominant genes, blaNDM 107(88.4%). Others included blaIMP 7 (5.7%), blaOXA-48 5(4.1%), blaVIM 2 (1.6%) and blaKPC 0 (0%). Co- resistance genes with NDM producing GNB were detected in 87 (81.3%) of all blaNDM positive isolates. A significant association between phenotypic and genotypic resistance was observed (P- value < 0.001). NDM-1 was the most sub type was observed in 75 isolates (70 %), other subtypes were NDM- 5 and NDM-6. Infections due to Carbapenem resistant GNB are increasing at SUH, with the blaNDM being the prevalent genes among clinical isolates and belong to the Indian lineage.Conclusions:The frequency of carbapenemase producing bacilli was found to be improperly high in Khartoum hospitals. NDM was found to be the most prevalent carbapenemase gene among clinical isolates. Close surveillance across all hospitals in Sudan is required. The relative distribution of Carbapenemase genes among GNB in nosocomial infections in Africa needs to be defined.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2020
Admission routes1
Has abstractyes

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