ArticleScientific reports2024
Failure mode and effects analysis-based strategies for controlling multidrug-resistant organism infections in cancer patients.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
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Who cites it
3 citing papers in PubMed.
- Clinical risk factors for multidrug-resistant organism infections in postoperative gastric cancer patients: an ICU-based retrospective analysis.BMC infectious diseases · 2026Article
- Failure mode and effects analysis nursing model improves recovery and quality of life post-laparoscopic extended radical colectomy for colorectal cancer.World journal of gastrointestinal surgery · 2026Article
- Using failure mode and effects analysis for risk management of anesthetic and class I psychotropic drugs in inpatient pharmacy: a pilot study.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
In the context of advancing medical procedures, postoperative infections in cancer patients, particularly those involving multidrug-resistant organisms, have become a significant clinical concern. This study aims to comprehensively and systematically evaluate the effectiveness of infection prevention and control for multidrug-resistant organisms (MDROs) in postoperative cancer patients using Failure Mode and Effects Analysis (FMEA). This study was conducted in a tertiary A-level cancer specialty hospital in China, employing Failure Mode and Effects Analysis (FMEA) to assess the risks of hospital infections. Intervention measures were implemented for high-risk and medium-high-risk factors. Through the hospital's infection information system, data on patients who underwent surgical treatment from 2017 to 2022 were extracted. Data from 2017 to 2019 served as the control group, and data from 2020 to 2022 as the intervention group, to compare the changes in hospital infection incidence and MDRO infection incidence before and after the intervention. Categorical data were described in terms of frequency and percentage. The chi-square test was utilized for statistical inference to assess the differences in infection rates before and after the intervention. Prior to the intervention (2017-2019), the incidence rate of hospital infections was 1.66%, which decreased to 1.22% after the intervention (2020-2022), showing a statistically significant difference (χ
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Registered trials
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