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Record W2141840620 · doi:10.1001/jama.2013.282426

Calcium-Channel Blocker–Clarithromycin Drug Interactions and Acute Kidney Injury

2013· article· en· W2141840620 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJAMA · 2013
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of TorontoWestern UniversitySt. Michael's HospitalLondon Health Sciences CentreLawson Health Research InstituteInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsMedicineClarithromycinAzithromycinAmlodipineCalcium channel blockerNifedipineInternal medicinePopulationAcute kidney injuryPharmacologyCalciumBlood pressureAntibiotics

Abstract

fetched live from OpenAlex

IMPORTANCE: Calcium-channel blockers are metabolized by the cytochrome P450 3A4 (CYP3A4; EC 1.14.13.97) enzyme. Blood concentrations of these drugs may rise to harmful levels when CYP3A4 activity is inhibited. Clarithromycin is an inhibitor of CYP3A4 and azithromycin is not, which makes comparisons between these 2 macrolide antibiotics useful in assessing clinically important drug interactions. OBJECTIVE: To characterize the risk of acute adverse events following coprescription of clarithromycin compared with azithromycin in older adults taking a calcium-channel blocker. DESIGN, SETTING, AND PARTICIPANTS: Population-based retrospective cohort study in Ontario, Canada, from 2003 through 2012 of older adults (mean age, 76 years) who were newly coprescribed clarithromycin (n = 96,226) or azithromycin (n = 94,083) while taking a calcium-channel blocker (amlodipine, felodipine, nifedipine, diltiazem, or verapamil). MAIN OUTCOMES AND MEASURES: Hospitalization with acute kidney injury (primary outcome) and hospitalization with hypotension and all-cause mortality (secondary outcomes examined separately). Outcomes were assessed within 30 days of a new coprescription. RESULTS: There were no differences in measured baseline characteristics between the clarithromycin and azithromycin groups. Amlodipine was the most commonly prescribed calcium-channel blocker (more than 50% of patients). Coprescribing clarithromycin vs azithromycin with a calcium-channel blocker was associated with a higher risk of hospitalization with acute kidney injury (420 patients of 96,226 taking clarithromycin [0.44%] vs 208 patients of 94,083 taking azithromycin [0.22%]; absolute risk increase, 0.22% [95% CI, 0.16%-0.27%]; odds ratio [OR], 1.98 [95% CI, 1.68-2.34]). In a subgroup analysis, the risk was highest with dihydropyridines, particularly nifedipine (OR, 5.33 [95% CI, 3.39-8.38]; absolute risk increase, 0.63% [95% CI, 0.49%-0.78%]). Coprescription with clarithromycin was also associated with a higher risk of hospitalization with hypotension (111 patients of 96,226 taking clarithromycin [0.12%] vs 68 patients of 94,083 taking azithromycin [0.07%]; absolute risk increase, 0.04% [95% CI, 0.02%-0.07%]; OR, 1.60 [95% CI, 1.18-2.16]) and all-cause mortality (984 patients of 96,226 taking clarithromycin [1.02%] vs 555 patients of 94,083 taking azithromycin [0.59%]; absolute risk increase, 0.43% [95% CI, 0.35%-0.51%]; OR, 1.74 [95% CI, 1.57-1.93]). CONCLUSIONS AND RELEVANCE: Among older adults taking a calcium-channel blocker, concurrent use of clarithromycin compared with azithromycin was associated with a small but statistically significant greater 30-day risk of hospitalization with acute kidney injury. These findings support current safety warnings regarding concurrent use of CYP3A4 inhibitors and calcium-channel blockers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.001

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 head0.060
GPT teacher head0.409
Teacher spread0.349 · 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