Evidence map›Paper›PMID 35235113›Full record

ArticleInternational journal of clinical pharmacy2022

Potential drug-drug interactions of immunosuppressants in kidney transplant recipients: comparison of drug interaction resources.

Aysel Pehlivanli, Rezzan Eren-Sadioglu, Merve Aktar, Sahin Eyupoglu, Sule Sengul, Kenan Keven, Sehsuvar Erturk, Bilgen Basgut, Arif Tanju Ozcelikay

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Article in International journal of clinical pharmacy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Assessment of potential drug interactions in rheumatology: a comparative study of decision support software.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Aysel PehlivanliFaculty of Pharmacy, Department of Clinical Pharmacy, Ankara University, Ankara, Turkey. pehlivanli@ankara.edu.tr.ORCID http://orcid.org/0000-0003-3276-0162
Rezzan Eren-SadiogluSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Merve AktarSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Sahin EyupogluSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Sule SengulSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Kenan KevenSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Sehsuvar ErturkSchool of Medicine, Department of Nephrology, Ankara University, Ankara, Turkey.
Bilgen BasgutFaculty of Pharmacy, Department of Pharmacology, Baskent University, Ankara, Turkey.
Arif Tanju OzcelikayFaculty of Pharmacy, Department of Pharmacology, Ankara University, Ankara, Turkey.
Ankara University · TRBaşkent University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Drug-drug interactions are frequently observed in kidney transplant recipients due to polypharmacy and use of immunosuppressants. However, there is only one study evaluating clinically relevant potential drug-drug interactions of immunosuppressants specially in kidney transplant recipients by means of online databases and Stockleys Drug Interactions, as a gold standard. Aim This study aimed to compare four online databases used frequently to determined clinically relevant potential drug-drug interactions of immunosuppressants in kidney transplant recipients according to the Renal Drug Handbook. Method This was a descriptive cross-sectional study conducted between October 1, 2019, and March 18, 2020, in the nephrology ward of Ankara University School of the Medicine, Ibn-i Sina Hospital. In total, 52 adult patients' discharge prescriptions were retrieved from their medical records and analyzed retrospectively. Micromedex®, Lexicomp®, Medscape, and Drugs.com databases were used to evaluate drug interactions. The Renal Drug Handbook was used as a gold standard to do specificity and sensitivity analysis. Results A total of 127 potential drug-drug interactions between the immunosuppressants and co-medications were detected by at least one online database. 32 (25.2%) of these were approved as clinically relevant potential drug-drug interactions by the Renal Drug Handbook. Lexicomp® and Drugs.com have exhibited the highest sensitivity (0.72 and 0.75) while Micromedex® has shown the highest specifity (0.83). Furthermore, the highest positive predictive value has been observed in Micromedex® (0.53). Micromedex® and Medscape had the highest negative predictive value (0.83 and 0.82). However, the kappa value of all was low. The values of inter-rater agreement (Kappa index) between online databases and the Renal Drug Handbook were weak (range 0.05-0.36). In addition, only 11 (8.7%) of potential drug-drug interactions were identified by all online databases. Conclusion This study showed that there was a weak compatibility between each database examined and the Renal Drug Handbook to detect clinically relevant potential drug-drug interactions for immunosuppressants in kidney transplant recipients. Therefore, we suggest that although databases might be practical to take a quick glance in detection of potential drug-drug interactions between immunosuppressants and co-medications, the data should be evaluated in detail and interpreted with caution in combination with a reference book like Renal Drug Handbook.

Indexed as

Immunosuppressive AgentsKidney TransplantationAdultCross-Sectional StudiesDrug InteractionsHumansRetrospective StudiesImmunosuppressive AgentsDatabasesDrug-drug interactionsKidney transplant recipientsThe renal drug handbook

Identifiers

PMID35235113
OpenAlexW4214837922

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.