Evidence map›Paper›PMID 38890711›Full record

Observational studyAntimicrobial resistance and infection control2024

Automated surveillance of antimicrobial consumption in intensive care, northern Sweden: an observational case study.

Andreas Winroth, Mattias Andersson, Peter Fjällström, Anders F Johansson, Alicia Lind

Abstract readObservational Study
In one paragraph

Observational study in Antimicrobial resistance and infection control, 2024. 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

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

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

5 authors.

Andreas WinrothDepartment of Clinical Microbiology, Umeå University, SE-90187, Umeå, Sweden. andreas.winroth@umu.se.
Mattias AnderssonCenter for Intensive Care (IT unit), Norrlands universitetssjukhus, 90185, Umeå, SE, Sweden.
Peter FjällströmDepartment of Clinical Microbiology, Umeå University, SE-90187, Umeå, Sweden.
Anders F Johansson *Department of Clinical Microbiology, Umeå University, SE-90187, Umeå, Sweden.ORCID 0000-0003-0548-5943
Alicia Lind *Department of Diagnostics and Intervention, Umeå University, SE-90187, Umeå, Sweden.ORCID 0000-0003-0309-1852

Funding

Västerbotten Läns Landsting RV-866001Västerbotten Läns Landsting RV-939456VINNOVA 2021-02699
6 · The paper itself

Abstract

backgroundThe digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.

objectivesDescribe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.

methodsAn automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.

resultsThere were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.

conclusionWe introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.

Indexed as

Intensive Care UnitsAgedAnti-Bacterial AgentsAntimicrobial StewardshipCOVID-19Electronic Health RecordsFemaleHumansMaleMiddle AgedSARS-CoV-2SwedenAnti-Bacterial AgentsAntibioticsAntimicrobial consumptionAntimicrobial resistanceAntimicrobial stewardshipAutomated surveillanceIntensive care

Identifiers

PMID38890711
PMCPMC11186282

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.