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Record W4353014842 · doi:10.1089/sur.2022.277

Evaluation of the Risk Factors of Nosocomial Pneumonia and the Prevalence of Antibiotic Resistance in Trauma Patients in Need of Immediate Intervention

2023· article· en· W4353014842 on OpenAlexaboutno aff
Mahnaz Yadollahi, Amir Hossein Shams, Mojtaba Norouzi, Monireh Feizi

Bibliographic record

VenueSurgical Infections · 2023
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePneumoniaVentilator-associated pneumoniaProspective cohort studyAcinetobacter baumanniiMechanical ventilationIntensive care medicineEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: Pneumonia is the most common nosocomial infection reported worldwide in intensive care units. This study aimed to evaluate the risk factors of nosocomial pneumonia and the frequency of antibiotic resistance in trauma patients who need immediate intervention. Patients and Methods: This prospective cohort study was conducted in Shahid Rajaei Trauma Hospital in Shiraz between 2020 and 2021. All the trauma patients who needed immediate intervention (levels 1 and 2 based on the Canadian Emergency Department Triage and Acuity Scale) and had no symptoms of infection were included. Patients who were discharged or died before 48 hours were excluded. Results: The results demonstrated that major trauma (Injury Severity Score [ISS] ≥16), intubation, and use of invasive mechanical ventilation increase nosocomial pneumonia and death rate. The most common causes of nosocomial infections were Acinetobacter baumannii (23%) and coagulase-negative staphylococcus (18.5%). The highest levels of antibiotic resistance were related to cefoxitin, erythromycin, ciprofloxacin, and trimethoprim-sulfamethoxazole. Conclusions: Major trauma, intubation, and invasive mechanical ventilation were the effective factors in the development of nosocomial pneumonia. Continuous monitoring for mentioned risk factors and strict surveillance of antibiotic prescription can decrease the prevalence of nosocomial infections and subsequent 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)0.002
metaresearch head score (Gemma)0.002
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 score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.025
GPT teacher head0.317
Teacher spread0.293 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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