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Record W2011617703 · doi:10.1017/s0950268805005583

Risk factors for typhoid fever among adult patients in Diyarbakir, Turkey

2005· article· en· W2011617703 on OpenAlexaff
Salih Hoşoğlu, Mustafa Kemal Çelen, Mehmet Faruk Geyik, Şerife Akalın, Celal Ayaz, Hamit Acemoğlu, Mark Loeb

Bibliographic record

VenueEpidemiology and Infection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTyphoid feverSalmonella typhiMedicineConditional logistic regressionLogistic regressionEnvironmental healthTransmission (telecommunications)Blood cultureVeterinary medicineCase-control studyInternal medicineVirologyBiologyMicrobiologyAntibiotics

Abstract

fetched live from OpenAlex

We conducted a case-control study to assess risk factors for typhoid fever in Diyarbakir, Turkey, a region where transmission of Salmonella typhi is endemic. We prospectively identified febrile patients from Diyarbakir and the surrounding area who were admitted to hospital. Cases were defined as patients who had S. typhi isolated from at least one blood culture. Sixty-four cases with blood culture-confirmed S. typhi were identified between May 2001 and May 2003. In total, 128 age- and sex-matched controls selected from neighbourhoods as cases were enrolled. We hypothesized that consumption of raw vegetables contaminated with sewage would be associated with an increased risk of typhoid fever. Conditional logistic regression modelling revealed that living in a crowded household (OR 3.31, 95% CI 1.58-6.92, P=0.002), eating cig kofte (a traditional raw food) (OR 5.29, 95% CI 2.20-12.69, P=0.000) and lettuce salad (OR 3.55, 95% CI 1.52-8.28, P=0.003) in the 15 days prior to symptoms onset was independently associated with typhoid fever. We conclude that living in a crowded household and consumption of raw vegetables outside the home increase the risk of typhoid fever in this region.

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)0.003
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 score0.026
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.000
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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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

Citations37
Published2005
Admission routes1
Has abstractyes

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