Evidence map›Paper›PMID 31157049›Full record

ArticleEuropean journal of hospital pharmacy : science and practice2018

Prevalence and predictors of potential drug-drug interactions in patients of internal medicine wards of a tertiary care hospital in India.

Yugandhar Bethi, Deepak Gopal Shewade, Tarun Kumar Dutta, Batmanabane Gitanjali

Abstract read
In one paragraph

Article in European journal of hospital pharmacy : science and practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Clinical Pertinence and Determinants of Potential Drug-Drug Interactions in Chronic Kidney Disease Patients: A Cross-sectional Study.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2024
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Yugandhar BethiDepartment of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.ORCID 0000-0002-5331-8309
Deepak Gopal ShewadeDepartment of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Tarun Kumar DuttaDepartment of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Batmanabane GitanjaliDepartment of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug-drug interactions are a major source of adverse drug events (ADEs). Polypharmacy, age and the number of comorbid conditions are important predictors of adverse drug interactions. ADEs account for up to 5% of hospital admissions per year and an increase in the length of hospital stay.

objectiveTo find the prevalence and predictors of potential drug-drug interactions (pDDIs) in patients admitted to the wards of an internal medicine department of a tertiary care hospital.

methodPatients admitted to internal medicine wards with prescriptions having more than one drug were selected. Demographic details including age, gender, number of comorbid conditions, number of drugs prescribed and the disease for which the patient was admitted were recorded in a case record form. Interactions were checked using Micromedex DrugReax software.

resultsA total of 939 patients were recruited for this study based on inclusion criteria. 433 prescriptions (46%) had one or more pDDIs, with a range of 1-13 drug interactions per prescription. A total of 1395 drug interactions were found, with 866 moderate drug interactions (62%), 435 major interactions (31.1%) and 89 minor interactions (6.3%). During the study period only three contraindicated drug combinations (0.2%) were recorded. A significant association (p<0.01) was found between the number of pDDIs and predictors, age and number of drugs.

conclusionA total of 433 prescriptions (46%) had one or more pDDIs. Older patients and those prescribed >6 drugs are at major risk for occurrence of pDDIs. Moderate severity interactions were the highest number followed by major severity interactions.

Indexed as

adverse drug eventadverse drug reactiondrug-drug interactionmedication safetypolypharmacy

Identifiers

PMID31157049
PMCPMC6319410

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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.