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Investigation of multiple nosocomial infections using a semi-Markov multi-state model.
Zhong, Xiao; Wang, Dong-Li; Xiao, Li-Hua; Liu, Yan; Yang, Shan-Wen; Mo, Lan-Fang; Wu, Qin-Fei; Lin, Mei; He, Lan-Fang; Luo, Xiao-Feng.
Affiliation
  • Zhong X; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China. 187197283@qq.com.
  • Wang DL; Testing Centre, Guangming District Centre for Disease Control and Prevention, Shenzhen, Guangdong, China.
  • Xiao LH; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Liu Y; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Yang SW; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Mo LF; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Wu QF; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Lin M; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • He LF; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
  • Luo XF; Infection Management Department, Shenzhen Guangming District People's Hospital, Shenzhen, Guangdong, 518106, China.
Antimicrob Resist Infect Control ; 13(1): 58, 2024 Jun 06.
Article de En | MEDLINE | ID: mdl-38845037
ABSTRACT

BACKGROUND:

The prevalence of multiple nosocomial infections (MNIs) is on the rise, however, there remains a limited comprehension regarding the associated risk factors, cumulative risk, probability of occurrence, and impact on length of stay (LOS).

METHOD:

This multicenter study includes all hospitalized patients from 2020 to July 2023 in two sub-hospitals of a tertiary hospital in Guangming District, Shenzhen. The semi-Markov multi-state model (MSM) was utilized to analyze risk factors and cumulative risk of MNI, predict its occurrence probability, and calculate the extra LOS of nosocomial infection (NI).

RESULTS:

The risk factors for MNI include age, community infection at admission, surgery, and combined use of antibiotics. However, the cumulative risk of MNI is lower than that of single nosocomial infection (SNI). MNI is most likely to occur within 14 days after admission. Additionally, SNI prolongs LOS by an average of 7.48 days (95% Confidence Interval, CI 6.06-8.68 days), while MNI prolongs LOS by an average of 15.94 days (95% CI 14.03-18.17 days). Furthermore, the more sites of infection there are, the longer the extra LOS will be.

CONCLUSION:

The longer LOS and increased treatment difficulty of MNI result in a heavier disease burden for patients, necessitating targeted prevention and control measures.
Sujet(s)
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Infection croisée / Durée du séjour Limites: Adult / Aged / Female / Humans / Male / Middle aged Pays/Région comme sujet: Asia Langue: En Journal: Antimicrob Resist Infect Control Année: 2024 Type de document: Article Pays d'affiliation: Chine

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Infection croisée / Durée du séjour Limites: Adult / Aged / Female / Humans / Male / Middle aged Pays/Région comme sujet: Asia Langue: En Journal: Antimicrob Resist Infect Control Année: 2024 Type de document: Article Pays d'affiliation: Chine