Evidence map›Paper›PMID 29201318›Full record

ArticleCaspian journal of internal medicine2017

Antibiotic resistance status and its costs in hematological patients: A two-year analysis.

Habip Gedik

Open access · greenAbstract read
In one paragraph

Article in Caspian journal of internal medicine, 2017. 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
0.6field-weighted citation impact, top 30% 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, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Prevalence ofIranian journal of pathology · 2018
    Article
  6. Article
  7. 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

1 author at 1 institution in 1 country.

Habip GedikDepartment of Infectious Diseases and Clinical MicrobiologyMinistry of Health Okmeydanı Training and Research Hospitalstanbul, Turkey.
Ministry of Health · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost frequently, empirical antibiotic therapy is immediately administered for patients with febrile neutropenia (FN). In this study, its aim was to assess the antibiotic resistance status and the cost of antibacterial agents in FN patients associated with hematological malignancies.

methodsThe cost of antibacterial agents used in FN episodes in patients with hematologic neoplasms followed-up at the Department of Hematology from November 2010 to November 2012 were analyzed retrospectively.

resultsIn the study period, 15 of 141 patients who were admitted to the hematology ward and ineligible for the study criteria were excluded. In total, 282 febrile episodes of 126 consecutive patients with neutropenia were retrospectively investigated. Imipenem was found to be the most commonly used among the antibacterial drugs as 1.16 patient daily dose (PDD)/100 patient-days, 117.16 is the mean defined daily dose (DDD) per month and US $73264.66 total cost per year, followed by meropenem, cefoperazone-sulbactam, and linezolid.

conclusionChoosing noncarbapenem-based antibacterial therapy for empirical treatment of FN until the growth of microorganisms and switching to carbapenem therapy subsequent to new radiological, or microbiological, or/ and clinical findings, the appropriate vancomycin use may decrease the cost of antibacterial agents in the treatment of FN episodes in patients with hematologic malignancies contributing to antimicrobial stewardship.

Indexed as

Anti-bacterial agentsCost analysisDrug resistance.Febrile neutropeniaHematologic neoplasms

Identifiers

PMID29201318
PMCPMC5686306
OpenAlexW2763113932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.