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Record W2921319768 · doi:10.1017/s0950268818003436

Annual relative increased in inpatient mortality from antimicrobial resistant nosocomial infections in Thailand

2019· article· en· W2921319768 on OpenAlexaff
Tuangrat Phodha, Arthorn Riewpaiboon, Kumthorn Malathum, Peter C. Coyte

Bibliographic record

VenueEpidemiology and Infection · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsInstitute for Work & HealthPublic Health OntarioUniversity of Toronto
FundersMahidol UniversityRoyal Golden Jubilee (RGJ) Ph.D. ProgrammeThailand Research FundUniversity of Oxford
KeywordsMedicineHazard ratioAcinetobacter baumanniiAntimicrobialAntibiotic resistanceRelative riskAcinetobacterRetrospective cohort studyConfoundingInternal medicinePseudomonas aeruginosaStaphylococcus aureusConfidence intervalAntibioticsMicrobiologyBacteriaBiology

Abstract

fetched live from OpenAlex

Antimicrobial resistance is a major health threat worldwide as it brings about poorer treatment outcome and places economic burden to the society. This study aims to estimate the annual relative increased in inpatient mortality from antimicrobial resistant (AMR) nosocomial infections (NI) in Thailand. A retrospective cohort study was conducted at Ramathibodi Hospital, Bangkok, Thailand, over 2008-2012. Survival model was used to estimate the hazard ratio of mortality of AMR relative to those patients without resistance (non-AMR) after controlling for nine potential confounders. The majority of NI (73.80%) were caused by AMR bacteria over the study period. Patients in the AMR and non-AMR groups had similar baseline clinical characteristics. Relative to patients in the non-AMR group, the expected hazard ratios of mortality for patients in the AMR group with Acinetobacter baumannii, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus were 1.92 (95% CI 0.10-35.52), 1.25 (95% CI 0.08-20.29), 1.60 (95% CI 0.13-19.10) and 1.84 (95% CI 0.04-95.58), respectively. In the complete absence of AMR bacteria, this study estimated that annually, in Thailand, there would be 111 295 fewer AMR cases and 48 258 fewer deaths.

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 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)0.001
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 score0.014
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.270
Teacher spread0.255 · 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 teacher head, 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".

Quick stats

Citations17
Published2019
Admission routes1
Has abstractyes

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