Evidence map›Paper›PMID 40352207›Full record

ArticleNarra J2025

Antibiotic use patterns and factors associated with leukocyte decrease in COVID-19 patients with suspected secondary infections: A cross-sectional study in Indonesia.

Pricella A Ginting, Tjokorde Ia Padmasawitri, Nadia Hanum, Raden D Nurhayati, Arto Y Soeroto, Lia Amalia

Abstract read
In one paragraph

Article in Narra J, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Pricella A GintingDepartment of Pharmacology-Clinical Pharmacy, School of Pharmacy, Institut Teknologi Bandung, Bandung, Indonesia.
Tjokorde Ia PadmasawitriDepartment of Pharmacology-Clinical Pharmacy, School of Pharmacy, Institut Teknologi Bandung, Bandung, Indonesia.
Nadia HanumDepartment of Pharmacology-Clinical Pharmacy, School of Pharmacy, Institut Teknologi Bandung, Bandung, Indonesia.
Raden D NurhayatiDepartment of Internal Medicine Dr. H. A Rotinsulu Lung Hospital, Bandung, Indonesia.
Arto Y SoerotoDepartment of Internal Medicine, Hasan Sadikin Hospital, Bandung, Indonesia.
Lia AmaliaDepartment of Pharmacology-Clinical Pharmacy, School of Pharmacy, Institut Teknologi Bandung, Bandung, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotics are frequently prescribed to coronavirus disease 2019 (COVID-19) patients, often without evidence of bacterial superinfection, increasing the risk of antibiotic resistance and posing a public health threat. The aim of this study was to evaluate antibiotic prescribing patterns in COVID-19 patients with suspected secondary infections and to assess the association between antibiotic use and clinical outcomes, particularly leukocyte count. The study analyzed 376 hospitalized COVID-19 patients from two hospitals in Bandung, Indonesia, between 2020 and 2022. All included patients were aged ≥17 years with confirmed COVID-19, leukocyte count >11,000 μg/L, and received antibiotic therapy. The Anatomical Therapeutic Chemical/Defined Daily Dose (ATC/DDD) and drug utilization (DU) 90% were used to assess prescribing patterns. The patients' demographic characteristics, clinical and culture results were also collected. Our data indicated that most patients received multiple antibiotics (>2), with prescribing patterns significantly associated with age, confirmed bacterial pathogen, length of hospital stay and having tuberculosis infection. The most frequently identified pathogens included Gram-positive bacteria

Indexed as

Anti-Bacterial AgentsBacterial InfectionsCoinfectionCOVID-19COVID-19 Drug TreatmentPractice Patterns, Physicians'AdultAgedCross-Sectional StudiesFemaleHumansIndonesiaLeukocyte CountMaleMiddle AgedSARS-CoV-2Anti-Bacterial AgentsAMRantibiotic useCOVID-19Defined Daily Dosedrug utilization 90%

Identifiers

PMID40352207
PMCPMC12059868

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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.