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The problem of professional hemocontact infections in the Saratov Region

2020· article· en· W3111512099 on OpenAlexaboutno aff
А. А. Панина, Lidiya A. Sycheva

Bibliographic record

VenueRussian Journal of Occupational Health and Industrial Ecology · 2020
Typearticle
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadIgnoranceDismissalQuarter (Canadian coin)MedicineSpecialtyFamily medicineIncidence (geometry)OverworkAction (physics)Medical emergency

Abstract

fetched live from OpenAlex

Introduction. The increase in the number of emergency situations (ES) in medical institutions in Russia actualizes the study of the state of this problem in different territories in order to optimize regional programs for the prevention of occupational diseases of medical workers, including hemocontact infections. The aim of study is to identify possible reasons for the lack of occupational morbidity of hemocontact infections in the Saratov Region. Materials and methods. To determine the frequency, types and possible causes of ES, the procedure for their registration, and the awareness of medical workers about the algorithm of actions in case of their development, 82 doctors in the specialties of obstetrician-gynecologist and surgeon (39 and 43 people, respectively) were interviewed at a multi-specialty hospital in Saratov (continuous sampling method). Results. The presence of ES in the practice of the majority of doctors surveyed (59%) was revealed, and 19% of respondents had multiple as (5 or more times). Most often, as occurs during the transfer and reception of acute surgical instruments. Among the most likely risk factors for developing as are high workload, emotional overload, and working at night. A quarter of aces do not register in the injury log, which is due to lack of time (42%) and the log itself (25%), ignorance of the need for this action (17%), fear of dismissal (8%). Conclusions. One of the main possible reasons for the lack of professional incidence of hemocontact infections is the lack of awareness of doctors about the algorithm of action in the event of an emergency at the workplace, in some cases-the lack of conditions for the implementation of this algorithm.

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)0.003
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: none
Teacher disagreement score0.511
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.139
GPT teacher head0.398
Teacher spread0.259 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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