Abstract
Title: Association rule analysis to evaluate frequent drug combinations associated with acute kidney injury in older adults
Prasad S Nishtala, PhD1; Te-yuan Chyou, PhD2. 1Department of Pharmacy and Pharmacology, University of Bath, Bath BA2 7AY, United Kingdom; 2 Department of Biochemistry, University of Otago, Dunedin, New Zealand
Background: Older adults are at an increased risk of AKI because of aging, multiple comorbidities, and polypharmacy.
Objectives: The aim of this case-crossover study was to apply association rule analysis to ascertain drug combinations contributing to the risk of acute kidney injury (AKI) in adults aged 65 years and older.
Method: We sourced a nationwide representative sample of New Zealanders aged ≥65 years from the pharmaceutical collections and hospital discharge information. Prescription records (2005-2015) of drugs of interest were sourced from New Zealand pharmaceutical collections (Pharms). We classified medication exposure, as a binary variable, at individual drug level belonging to medication classes including antimicrobials, antihistamines, diuretics, opioids, non-steroidal anti-inflammatory medications. Several studies have associated the drugs of interest from these medication classes with AKI in older adults. The first-time coded diagnosis of AKI was extracted from the National Minimal Dataset (NMDS). A unique patient identifier linked the prescription dataset to the event dataset, to set up a case-crossover cohort, indexed at the first AKI event. Association rules were then applied to identify frequent drug combinations in the case and the control periods (l-day with a 35-day washout period), and the association of AKI with each frequent drug combination was tested by computing a matched odds-ratio (MOR) and its 95% confidence interval (CI).
Results: We identified 55747 individuals (mean age 82.14) from 2005 to 2014 with incident AKI and exposed to at least one of the drugs of interest. Association rules identified several drug classes including antimicrobials, nonsteroidal anti-inflammatory medications and opioids are associated with AKI. Association rules revealed that frequently used drug combinations associated with AKI are trimethoprim (MOR=1.68; 95%CI= [1.54-1.80]), ondansetron (MOR=1.43; 95%CI= [1.25-1.64]), codeine phosphate plus metoclopramide (MOR=1.37; 95%CI= [1.11-1.63]), and norfloxacin (MOR=1.24; 95%CI [1.05-1.42]).
Conclusion: We applied association rules, a novel methodology, to big data to ascertain drug combinations associated with adverse drug events. Association rules uncovered previously implicated drug classes such as opioids and antibiotics that increase the risk of AKI in older adults. The finding that ondansetron increases the risk of AKI requires further investigation.
Key words: medications; case-crossover; pharmacoepidemiology; older people, acute kidney injury; association rule analysis
Prasad S Nishtala, PhD1; Te-yuan Chyou, PhD2. 1Department of Pharmacy and Pharmacology, University of Bath, Bath BA2 7AY, United Kingdom; 2 Department of Biochemistry, University of Otago, Dunedin, New Zealand
Background: Older adults are at an increased risk of AKI because of aging, multiple comorbidities, and polypharmacy.
Objectives: The aim of this case-crossover study was to apply association rule analysis to ascertain drug combinations contributing to the risk of acute kidney injury (AKI) in adults aged 65 years and older.
Method: We sourced a nationwide representative sample of New Zealanders aged ≥65 years from the pharmaceutical collections and hospital discharge information. Prescription records (2005-2015) of drugs of interest were sourced from New Zealand pharmaceutical collections (Pharms). We classified medication exposure, as a binary variable, at individual drug level belonging to medication classes including antimicrobials, antihistamines, diuretics, opioids, non-steroidal anti-inflammatory medications. Several studies have associated the drugs of interest from these medication classes with AKI in older adults. The first-time coded diagnosis of AKI was extracted from the National Minimal Dataset (NMDS). A unique patient identifier linked the prescription dataset to the event dataset, to set up a case-crossover cohort, indexed at the first AKI event. Association rules were then applied to identify frequent drug combinations in the case and the control periods (l-day with a 35-day washout period), and the association of AKI with each frequent drug combination was tested by computing a matched odds-ratio (MOR) and its 95% confidence interval (CI).
Results: We identified 55747 individuals (mean age 82.14) from 2005 to 2014 with incident AKI and exposed to at least one of the drugs of interest. Association rules identified several drug classes including antimicrobials, nonsteroidal anti-inflammatory medications and opioids are associated with AKI. Association rules revealed that frequently used drug combinations associated with AKI are trimethoprim (MOR=1.68; 95%CI= [1.54-1.80]), ondansetron (MOR=1.43; 95%CI= [1.25-1.64]), codeine phosphate plus metoclopramide (MOR=1.37; 95%CI= [1.11-1.63]), and norfloxacin (MOR=1.24; 95%CI [1.05-1.42]).
Conclusion: We applied association rules, a novel methodology, to big data to ascertain drug combinations associated with adverse drug events. Association rules uncovered previously implicated drug classes such as opioids and antibiotics that increase the risk of AKI in older adults. The finding that ondansetron increases the risk of AKI requires further investigation.
Key words: medications; case-crossover; pharmacoepidemiology; older people, acute kidney injury; association rule analysis
| Original language | English |
|---|---|
| Pages | 425-425 |
| Number of pages | 1 |
| Publication status | Published - 1 Aug 2019 |