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Record W2415555123 · doi:10.26719/2015.21.4.287

Predictive factors of death in patients with tuberculosis: a nested case–control study

2015· article· en· W2415555123 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEastern Mediterranean Health Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsMedicineTuberculosisNested case-control studyPsychological interventionLogistic regressionCause of deathDiseaseGynecologyPediatricsInternal medicineCase-control studyPathology

Abstract

fetched live from OpenAlex

Tuberculosis is one of the main causes of death worldwide. This study aimed to determine predictive factors for death in patients with tuberculosis to set priorities for public heath interventions to reduce mortality in these patients. This nested case-control study was carried out in Mazandaran province of Islamic Republic of Iran among tuberculosis patients who were treated during 2002-2009. Each deceased patient was individually matched with a control patient according to sex, age, area of involvement and time of follow-up. Potential risk factors for death were evaluated using multivariate conditional logistic regression models. From 2206 patients 376 cases and 376 matched controls were selected. Only positive serology for HIV (OR = 19.1), history of kidney disease (OR = 6.81) and use of immunosuppressant drugs (OR = 3.96) significantly increased the risk of death in tuberculosis patients. These potentially modifiable risk factors could be taken into account in preventive interventions for tuberculosis patients in our country.

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.

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: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.073
GPT teacher head0.358
Teacher spread0.285 · 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