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Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Drug Utilization Pattern in Patients with Congestive Heart Failure at A Tertiary Care Teaching Hospital: A Cross-Sectional Study

Authors: Dr Harshkumar Kirankumar Brahmbhatt , Dr Aditi Bhandari , Dr Archana Jain , Dr Arvind Singh Tanwar , Dr. Rahul Damor , Dr Jatin Prajapati;

Drug Utilization Pattern in Patients with Congestive Heart Failure at A Tertiary Care Teaching Hospital: A Cross-Sectional Study

Abstract

Background: Congestive heart failure (CHF) is a major public health problem associated with high morbidity, mortality, and frequent hospitalizations. Rational prescribing and evaluation of drug utilization patterns are essential to ensure optimal therapeutic outcomes and adherence to guideline-directed medical therapy. Objectives : To evaluate the drug utilization pattern in patients with congestive heart failure at a tertiary care teaching hospital using WHO prescribing indicators and ATC/DDD methodology. Methods: This cross-sectional observational study was conducted in the Department of Cardiology of a tertiary care teaching hospital. A total of 156 patients diagnosed with congestive heart failure were included. Data were collected using a structured case record form. Drug utilization was analyzed using WHO core prescribing indicators. Drugs were classified according to the Anatomical Therapeutic Chemical (ATC) classification system, and quantitative analysis was performed using the Defined Daily Dose (DDD) methodology. Prescribed Daily Dose (PDD) to DDD ratios were calculated to assess prescribing trends. Results: Out of 156 patients, the majority were males and elderly individuals. Heart failure with reduced ejection fraction (HFrEF) was observed in 98 (62.82%) patients, heart failure with mildly reduced ejection fraction (HFmrEF) in 38 (24.36%) patients, and heart failure with preserved ejection fraction (HFpEF) in 20 (12.82%) patients. The average number of drugs prescribed per encounter was 6.8 ± 1.9. Diuretics were prescribed in 142 (91.03%) patients, beta-blockers in 136 (87.18%), angiotensin receptor–neprilysin inhibitors (ARNIs) in 124 (79.49%), antiplatelet agents in 118 (75.64%), and statins in 131 (83.97%) patients. All drugs (100%) were prescribed by generic name. The percentage of encounters with antibiotics prescribed was 0%. ATC/DDD analysis showed variation between prescribed daily dose and WHO defined daily dose for certain medications. The PDD:DDD ratio for atorvastatin was 2.89, suggesting prescribing at doses higher than the WHO defined daily dose, possibly reflecting high-intensity statin therapy. Conclusion: The study demonstrated that multidrug therapy was commonly prescribed in accordance with guideline-directed medical therapy for congestive heart failure. Drug utilization patterns were largely rational and consistent with standard treatment recommendations. Continuous monitoring using WHO prescribing indicators and ATC/DDD methodology can further promote rational drug use and optimize patient care

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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