The confounding role of common diabetes medications in developing acute renal failure: A data mining approach with emphasis on drug-drug interactions. (1st June 2019)
- Record Type:
- Journal Article
- Title:
- The confounding role of common diabetes medications in developing acute renal failure: A data mining approach with emphasis on drug-drug interactions. (1st June 2019)
- Main Title:
- The confounding role of common diabetes medications in developing acute renal failure: A data mining approach with emphasis on drug-drug interactions
- Authors:
- Davazdahemami, Behrooz
Delen, Dursun - Abstract:
- Highlights: An extent data mining approach is extended to assess the confounding role of drugs. General confounding role of diabetes drugs in developing renal failure is identified. Potential drug-drug interactions significantly modify the confounding role of drugs. Findings explain the inconsistent effects of diabetes drugs reported in prior research. Abstract: Longstanding diabetes mellitus is today known as the primary reason for kidney failure in the patients having that condition. While the prior research has studied the confounding role of some frequently prescribed diabetes medications in developing acute renal failure, some rarely prescribed medications are still under-studied in this regard. In addition, even for those drugs studied in the past, inconsistent findings have been reported. In the present study, by extending a data mining framework from the prior research and equipping that with some standard statistical metric from the medical literature we investigate the general confounding role of the common diabetes medications in developing acute renal failure in a large group of patients with diabetes mellitus (Type II). In addition, we assess the stability of the identified confounding roles by taking into account the potential drug-drug interactions between those diabetes medications with a group of drugs already known to have negative effect on the kidney function. Our results suggest the general dominant confounding role for each of the diabetes medications,Highlights: An extent data mining approach is extended to assess the confounding role of drugs. General confounding role of diabetes drugs in developing renal failure is identified. Potential drug-drug interactions significantly modify the confounding role of drugs. Findings explain the inconsistent effects of diabetes drugs reported in prior research. Abstract: Longstanding diabetes mellitus is today known as the primary reason for kidney failure in the patients having that condition. While the prior research has studied the confounding role of some frequently prescribed diabetes medications in developing acute renal failure, some rarely prescribed medications are still under-studied in this regard. In addition, even for those drugs studied in the past, inconsistent findings have been reported. In the present study, by extending a data mining framework from the prior research and equipping that with some standard statistical metric from the medical literature we investigate the general confounding role of the common diabetes medications in developing acute renal failure in a large group of patients with diabetes mellitus (Type II). In addition, we assess the stability of the identified confounding roles by taking into account the potential drug-drug interactions between those diabetes medications with a group of drugs already known to have negative effect on the kidney function. Our results suggest the general dominant confounding role for each of the diabetes medications, but also suggests that these roles are unstable across various prescription combinations due to potential drug-drug interactions, thereby provide an explanation for the inconsistent findings in the literature. … (more)
- Is Part Of:
- Expert systems with applications. Volume 123(2019)
- Journal:
- Expert systems with applications
- Issue:
- Volume 123(2019)
- Issue Display:
- Volume 123, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 123
- Issue:
- 2019
- Issue Sort Value:
- 2019-0123-2019-0000
- Page Start:
- 168
- Page End:
- 177
- Publication Date:
- 2019-06-01
- Subjects:
- Adverse drug reactions -- Itemset mining -- Diabetes -- Acute renal failure -- Drug-drug interactions
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2019.01.006 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9540.xml