Evidence map›Paper›PMID 40687122›Full record

ArticleFrontiers in public health2025

Evaluation of the disease burden of nosocomial infection among inpatients in a cancer hospital based on propensity score matching.

Jiayang Tang, Jiang Yuan, Hui Wang, Qin Huang, Weiwei Yang, Qingqing Tian, Anran Liu, Hailin Zhang, Chunlin Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

9 authors.

Jiayang TangSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Jiang YuanSchool of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Hui WangSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Qin HuangSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Weiwei YangSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Qingqing TianSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Anran LiuSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Hailin ZhangSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Chunlin WuSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Oncology patients, as an immunocompromised population, are particularly susceptible to hospital-acquired infections (HAIs). This study aims to establish a scientifically sound model to estimate the disease burden associated with HAIs in oncology patients, providing valuable decision-making support for healthcare systems and public health management. Methods: Propensity score matching (PSM) was employed. Post-matching permutation tests were applied to compare hospitalization costs and lengths of stay between the HAIs and non-HAI groups, as well as between the multidrug-resistant bacteria (MDRO) infection group and non-MDRO group. Results: The results indicate that the average hospitalization cost in the HAIs group was 23.7% higher than the non-HAI groups, with a median difference of 12,417.6 CNY. Among various hospitalization expenses, the largest disparity was observed in the cost of Western medications, which had a median difference of 5,453.79 CNY, representing a 54.38% increase. The average length of hospital stay in the HAIs group was 1.33 times that of the control group. For the MDRO infection group, the average hospitalization cost exceeded that of the control group by 56.43%, with an absolute difference of 32,266.62 CNY. Additionally, the average length of hospital stay in the MDRO group was 42.11% longer, extending by 8 days. Conclusion: Both HAIs and MDRO infections significantly increase hospitalization duration and costs. The resulting disease burden is reflected in the direct escalation of health economic costs and the indirect effects of reduced hospital operational efficiency and heightened strain on the healthcare system. On this basis, we conclude that the funds for the prevention and control of HAIs and MDRO infections should be increased, and the measures for the prevention and control of HAIs should be implemented effectively, so as to reduce the direct and indirect economic burdens caused by HAIs and MDRO infections.

Indexed as

Cancer Care FacilitiesCost of IllnessCross InfectionInpatientsNeoplasmsAdultAgedFemaleHospitalizationHumansLength of StayMaleMiddle AgedPropensity Scoremultidrug-resistant bacterial infectionsnosocomial infectiononcology patientspropensity score matchingthe disease burden

Identifiers

PMID40687122
PMCPMC12271144

What Socratic holds

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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 Socratic graph.