Evidence map›Paper›PMID 33389974›Full record

ArticleAnnals of geriatric medicine and research2020

Development and Application of a Surveillance Method for Healthcare-Associated Infections in Long-Term Care Hospitals in Korea.

Sun Young Jeong, JeongHwa Choi, Jae Yeun Kim, Hyuk Ga

Open access · diamondAbstract read
In one paragraph

Article in Annals of geriatric medicine and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.1field-weighted citation impact, top 41% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

4 authors at 4 institutions in 1 country.

Sun Young JeongCollege of Nursing, Konyang University, Daejeon, Korea.
JeongHwa ChoiInfection Control Team, Kunkuk Universty Medical Center, Seoul, Korea.
Jae Yeun KimDepartment of Infection Control, Konyang University Hospital, Daejeon, Korea.
Hyuk GaInstitute of Geriatric Medicine, Incheon Eun-Hye Hospital, Incheon, Korea.
Konkuk University Medical Center · KRKonyang University · KRKonyang University Hospital · KRNa Eun Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study developed a surveillance method for healthcare-associated infections (HAIs) in long-term care hospitals (LTCHs) and investigated the current status of HAIs in LTCHs in Korea.

methodsWe applied the HAI-related surveillance criteria for long-term care facilities developed by McGeer in six LTCHs.

resultsThe 197 confirmed HAIs corresponded to incidence rates of 30.38/100 inpatients and 1.57/1,000 days of hospitalization and included 84 cases of respiratory tract infection (43.8%), 78 cases of systemic infection (40.6%), 24 cases of gastrointestinal tract infection (12.5%), and 6 cases of skin and soft tissue mucosal infection (2.1%). The subtypes included 78 cases of unexplained febrile illness (40.6%); 40 cases of pneumonia (20.8%); 27 cases of lower respiratory tract infection (14.1%); 21 cases of gastroenteritis (10.9%); 9 cases of influenza-like illness (4.7%); 8 cases of common cold or pharyngitis (4.2%); 4 cases of cellulitis, soft tissue, or wound infection (2.1%); 3 cases of Clostridium difficile infection (1.6%); 1 case of conjunctivitis (0.5%); and 1 case of fungal oral/perioral and skin infection (0.5%).

conclusionEstablishing an HAI surveillance method for LTCHs and identifying HAI rates and risk factors among LTCH patients may help prevent HAIs in LTCHs in Korea.

Indexed as

EpidemiologyHospital infectionsKoreaLong-term care

Identifiers

PMID33389974
PMCPMC7781959
OpenAlexW3113412279

What OpenQuestion holds

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LicenceCC BY-NC
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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.