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Record W53824121 · doi:10.1093/joneph/19.6.771

Effect of antitubercular medications on blood pressure control in chronic kidney disease patients with tuberculosis: a prospective cohort study

2006· article· en· W53824121 on OpenAlexaff
Ajay P. Sharma, Saubhik Sural, Amit Gupta, Amit X. Garg, Sanjeev Gulati, Raj Kumar Sharma

Bibliographic record

VenueJournal of Nephrology · 2006
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineInternal medicineKidney diseaseTuberculosisProspective cohort studyBlood pressureCohortAntihypertensive drugCohort studyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Previous anecdotal reports suggested a decrease in antihypertensive medication potency after starting antitubercular medications. This interaction could be unpredictable in presence of renal failure due to increased half-lives of most commonly used antihypertensive medications. METHODS: In a cohort study involving 135 patients with chronic kidney disease (CKD), 62 patients with tuberculosis star-ted on antitubercular medications (TB group) were prospectively compared with 73 CKD controls (with no TB and not on antitubercular medications) for a change in antihypertensive medications. Antihypertensive dose was converted to unit score. RESULTS: The TB group had a greater increase in antihypertensive medication dose as compared with controls (89% vs. 54%, p<0.0001). In absolute terms an overall increase in antihypertensive medications was observed in 60% of pa-tients in the TB group, with a 2-fold dose increase from the baseline (p<0.0001). Four patients from the TB group de-veloped a hypertensive emergency. In multivariate linear regression, the association between TB group and increase in antihypertensives remained significant ( beta =0.38; p<0.0001). CONCLUSIONS: In CKD patients, antihypertensive medication potency is reduced in TB patients on antitubercular the-rapy in a significant number of patients, to a clinically significant degree with a potential risk for hypertensive emergency.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.043
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.003
GPT teacher head0.238
Teacher spread0.234 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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